--- _id: '14084' abstract: - lang: eng text: "A central problem in computational statistics is to convert a procedure for sampling combinatorial objects into a procedure for counting those objects, and vice versa. We will consider sampling problems which come from Gibbs distributions, which are families of probability distributions over a discrete space Ω with probability mass function of the form μ^Ω_β(ω) ∝ e^{β H(ω)} for β in an interval [β_min, β_max] and H(ω) ∈ {0} ∪ [1, n].\r\nThe partition function is the normalization factor Z(β) = ∑_{ω ∈ Ω} e^{β H(ω)}, and the log partition ratio is defined as q = (log Z(β_max))/Z(β_min)\r\nWe develop a number of algorithms to estimate the counts c_x using roughly Õ(q/ε²) samples for general Gibbs distributions and Õ(n²/ε²) samples for integer-valued distributions (ignoring some second-order terms and parameters), We show this is optimal up to logarithmic factors. We illustrate with improved algorithms for counting connected subgraphs and perfect matchings in a graph." acknowledgement: We thank Heng Guo for helpful explanations of algorithms for sampling connected subgraphs and matchings, Maksym Serbyn for bringing to our attention the Wang-Landau algorithm and its use in physics. alternative_title: - LIPIcs article_number: '72' article_processing_charge: Yes author: - first_name: David G. full_name: Harris, David G. last_name: Harris - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Harris DG, Kolmogorov V. Parameter estimation for Gibbs distributions. In: 50th International Colloquium on Automata, Languages, and Programming. Vol 261. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023. doi:10.4230/LIPIcs.ICALP.2023.72' apa: 'Harris, D. G., & Kolmogorov, V. (2023). Parameter estimation for Gibbs distributions. In 50th International Colloquium on Automata, Languages, and Programming (Vol. 261). Paderborn, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ICALP.2023.72' chicago: Harris, David G., and Vladimir Kolmogorov. “Parameter Estimation for Gibbs Distributions.” In 50th International Colloquium on Automata, Languages, and Programming, Vol. 261. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. https://doi.org/10.4230/LIPIcs.ICALP.2023.72. ieee: D. G. Harris and V. Kolmogorov, “Parameter estimation for Gibbs distributions,” in 50th International Colloquium on Automata, Languages, and Programming, Paderborn, Germany, 2023, vol. 261. ista: 'Harris DG, Kolmogorov V. 2023. Parameter estimation for Gibbs distributions. 50th International Colloquium on Automata, Languages, and Programming. ICALP: International Colloquium on Automata, Languages, and Programming, LIPIcs, vol. 261, 72.' mla: Harris, David G., and Vladimir Kolmogorov. “Parameter Estimation for Gibbs Distributions.” 50th International Colloquium on Automata, Languages, and Programming, vol. 261, 72, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, doi:10.4230/LIPIcs.ICALP.2023.72. short: D.G. Harris, V. Kolmogorov, in:, 50th International Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. conference: end_date: 2023-07-14 location: Paderborn, Germany name: 'ICALP: International Colloquium on Automata, Languages, and Programming' start_date: 2023-07-10 date_created: 2023-08-20T22:01:14Z date_published: 2023-07-01T00:00:00Z date_updated: 2023-08-21T06:49:11Z day: '01' ddc: - '000' - '510' department: - _id: VlKo doi: 10.4230/LIPIcs.ICALP.2023.72 external_id: arxiv: - '2007.10824' file: - access_level: open_access checksum: 6dee0684245bb1c524b9c955db1e933d content_type: application/pdf creator: dernst date_created: 2023-08-21T06:45:16Z date_updated: 2023-08-21T06:45:16Z file_id: '14088' file_name: 2023_LIPIcsICALP_Harris.pdf file_size: 917791 relation: main_file success: 1 file_date_updated: 2023-08-21T06:45:16Z has_accepted_license: '1' intvolume: ' 261' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '07' oa: 1 oa_version: Published Version publication: 50th International Colloquium on Automata, Languages, and Programming publication_identifier: isbn: - '9783959772785' issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' status: public title: Parameter estimation for Gibbs distributions tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 261 year: '2023' ... --- _id: '13120' abstract: - lang: eng text: 'We formalized general (i.e., type-0) grammars using the Lean 3 proof assistant. We defined basic notions of rewrite rules and of words derived by a grammar, and used grammars to show closure of the class of type-0 languages under four operations: union, reversal, concatenation, and the Kleene star. The literature mostly focuses on Turing machine arguments, which are possibly more difficult to formalize. For the Kleene star, we could not follow the literature and came up with our own grammar-based construction.' acknowledgement: "Jasmin Blanchette: This research has received funding from the Netherlands Organization\r\nfor Scientific Research (NWO) under the Vidi program (project No. 016.Vidi.189.037, Lean Forward).\r\n__\r\nWe thank Vladimir Kolmogorov for making this collaboration possible. We\r\nthank Václav Končický for discussing ideas about the Kleene star construction. We thank Patrick Johnson, Floris van Doorn, and Damiano Testa for their small yet very valuable contributions to our code. We thank Eric Wieser for simplifying one of our proofs. We thank Mark Summerfield for suggesting textual improvements. We thank the anonymous reviewers for very helpful comments. Finally, we thank the Lean community for helping us with various technical issues and answering many questions. " alternative_title: - LIPIcs article_number: '15' article_processing_charge: No author: - first_name: Martin full_name: Dvorak, Martin id: 40ED02A8-C8B4-11E9-A9C0-453BE6697425 last_name: Dvorak orcid: 0000-0001-5293-214X - first_name: Jasmin full_name: Blanchette, Jasmin last_name: Blanchette citation: ama: 'Dvorak M, Blanchette J. Closure properties of general grammars - formally verified. In: 14th International Conference on Interactive Theorem Proving. Vol 268. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023. doi:10.4230/LIPIcs.ITP.2023.15' apa: 'Dvorak, M., & Blanchette, J. (2023). Closure properties of general grammars - formally verified. In 14th International Conference on Interactive Theorem Proving (Vol. 268). Bialystok, Poland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ITP.2023.15' chicago: Dvorak, Martin, and Jasmin Blanchette. “Closure Properties of General Grammars - Formally Verified.” In 14th International Conference on Interactive Theorem Proving, Vol. 268. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. https://doi.org/10.4230/LIPIcs.ITP.2023.15. ieee: M. Dvorak and J. Blanchette, “Closure properties of general grammars - formally verified,” in 14th International Conference on Interactive Theorem Proving, Bialystok, Poland, 2023, vol. 268. ista: 'Dvorak M, Blanchette J. 2023. Closure properties of general grammars - formally verified. 14th International Conference on Interactive Theorem Proving. ITP: International Conference on Interactive Theorem Proving, LIPIcs, vol. 268, 15.' mla: Dvorak, Martin, and Jasmin Blanchette. “Closure Properties of General Grammars - Formally Verified.” 14th International Conference on Interactive Theorem Proving, vol. 268, 15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, doi:10.4230/LIPIcs.ITP.2023.15. short: M. Dvorak, J. Blanchette, in:, 14th International Conference on Interactive Theorem Proving, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. conference: end_date: 2023-08-04 location: Bialystok, Poland name: 'ITP: International Conference on Interactive Theorem Proving' start_date: 2023-07-31 date_created: 2023-06-05T07:29:05Z date_published: 2023-07-27T00:00:00Z date_updated: 2023-09-25T11:04:29Z day: '27' ddc: - '000' department: - _id: GradSch - _id: VlKo doi: 10.4230/LIPIcs.ITP.2023.15 external_id: arxiv: - '2302.06420' file: - access_level: open_access checksum: 773a0197f05b67feaa6cb1e17ec3642d content_type: application/pdf creator: dernst date_created: 2023-08-07T11:55:43Z date_updated: 2023-08-07T11:55:43Z file_id: '13982' file_name: 2023_LIPIcS_Dvorak.pdf file_size: 715976 relation: main_file success: 1 file_date_updated: 2023-08-07T11:55:43Z has_accepted_license: '1' intvolume: ' 268' language: - iso: eng month: '07' oa: 1 oa_version: Published Version publication: 14th International Conference on Interactive Theorem Proving publication_identifier: eissn: - 1868-8969 isbn: - '9783959772846' publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' related_material: link: - relation: software url: https://github.com/madvorak/grammars/tree/publish scopus_import: '1' status: public title: Closure properties of general grammars - formally verified tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 268 year: '2023' ... --- _id: '14448' abstract: - lang: eng text: We consider the problem of solving LP relaxations of MAP-MRF inference problems, and in particular the method proposed recently in [16], [35]. As a key computational subroutine, it uses a variant of the Frank-Wolfe (FW) method to minimize a smooth convex function over a combinatorial polytope. We propose an efficient implementation of this subroutine based on in-face Frank-Wolfe directions, introduced in [4] in a different context. More generally, we define an abstract data structure for a combinatorial subproblem that enables in-face FW directions, and describe its specialization for tree-structured MAP-MRF inference subproblems. Experimental results indicate that the resulting method is the current state-of-art LP solver for some classes of problems. Our code is available at pub.ist.ac.at/~vnk/papers/IN-FACE-FW.html. article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Kolmogorov V. Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol 2023. IEEE; 2023:11980-11989. doi:10.1109/CVPR52729.2023.01153' apa: 'Kolmogorov, V. (2023). Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 2023, pp. 11980–11989). Vancouver, Canada: IEEE. https://doi.org/10.1109/CVPR52729.2023.01153' chicago: 'Kolmogorov, Vladimir. “Solving Relaxations of MAP-MRF Problems: Combinatorial in-Face Frank-Wolfe Directions.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2023:11980–89. IEEE, 2023. https://doi.org/10.1109/CVPR52729.2023.01153.' ieee: 'V. Kolmogorov, “Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vancouver, Canada, 2023, vol. 2023, pp. 11980–11989.' ista: 'Kolmogorov V. 2023. Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition vol. 2023, 11980–11989.' mla: 'Kolmogorov, Vladimir. “Solving Relaxations of MAP-MRF Problems: Combinatorial in-Face Frank-Wolfe Directions.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2023, IEEE, 2023, pp. 11980–89, doi:10.1109/CVPR52729.2023.01153.' short: V. Kolmogorov, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2023, pp. 11980–11989. conference: end_date: 2023-06-24 location: Vancouver, Canada name: 'CVPR: Conference on Computer Vision and Pattern Recognition' start_date: 2023-06-17 date_created: 2023-10-22T22:01:16Z date_published: 2023-08-22T00:00:00Z date_updated: 2023-10-31T12:01:24Z day: '22' department: - _id: VlKo doi: 10.1109/CVPR52729.2023.01153 external_id: arxiv: - '2010.09567' intvolume: ' 2023' language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.48550/arXiv.2010.09567' month: '08' oa: 1 oa_version: Preprint page: 11980-11989 publication: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition publication_identifier: isbn: - '9798350301298' issn: - 1063-6919 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: 'Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions' type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2023 year: '2023' ... --- _id: '10737' abstract: - lang: eng text: We consider two models for the sequence labeling (tagging) problem. The first one is a Pattern-Based Conditional Random Field (PB), in which the energy of a string (chain labeling) x=x1⁢…⁢xn∈Dn is a sum of terms over intervals [i,j] where each term is non-zero only if the substring xi⁢…⁢xj equals a prespecified word w∈Λ. The second model is a Weighted Context-Free Grammar (WCFG) frequently used for natural language processing. PB and WCFG encode local and non-local interactions respectively, and thus can be viewed as complementary. We propose a Grammatical Pattern-Based CRF model (GPB) that combines the two in a natural way. We argue that it has certain advantages over existing approaches such as the Hybrid model of Benedí and Sanchez that combines N-grams and WCFGs. The focus of this paper is to analyze the complexity of inference tasks in a GPB such as computing MAP. We present a polynomial-time algorithm for general GPBs and a faster version for a special case that we call Interaction Grammars. article_processing_charge: No article_type: original author: - first_name: Rustem full_name: Takhanov, Rustem id: 2CCAC26C-F248-11E8-B48F-1D18A9856A87 last_name: Takhanov - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Takhanov R, Kolmogorov V. Combining pattern-based CRFs and weighted context-free grammars. Intelligent Data Analysis. 2022;26(1):257-272. doi:10.3233/IDA-205623 apa: Takhanov, R., & Kolmogorov, V. (2022). Combining pattern-based CRFs and weighted context-free grammars. Intelligent Data Analysis. IOS Press. https://doi.org/10.3233/IDA-205623 chicago: Takhanov, Rustem, and Vladimir Kolmogorov. “Combining Pattern-Based CRFs and Weighted Context-Free Grammars.” Intelligent Data Analysis. IOS Press, 2022. https://doi.org/10.3233/IDA-205623. ieee: R. Takhanov and V. Kolmogorov, “Combining pattern-based CRFs and weighted context-free grammars,” Intelligent Data Analysis, vol. 26, no. 1. IOS Press, pp. 257–272, 2022. ista: Takhanov R, Kolmogorov V. 2022. Combining pattern-based CRFs and weighted context-free grammars. Intelligent Data Analysis. 26(1), 257–272. mla: Takhanov, Rustem, and Vladimir Kolmogorov. “Combining Pattern-Based CRFs and Weighted Context-Free Grammars.” Intelligent Data Analysis, vol. 26, no. 1, IOS Press, 2022, pp. 257–72, doi:10.3233/IDA-205623. short: R. Takhanov, V. Kolmogorov, Intelligent Data Analysis 26 (2022) 257–272. date_created: 2022-02-06T23:01:32Z date_published: 2022-01-14T00:00:00Z date_updated: 2023-08-02T14:09:41Z day: '14' department: - _id: VlKo doi: 10.3233/IDA-205623 external_id: arxiv: - '1404.5475' isi: - '000749997700015' intvolume: ' 26' isi: 1 issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1404.5475 month: '01' oa: 1 oa_version: Preprint page: 257-272 publication: Intelligent Data Analysis publication_identifier: eissn: - 1571-4128 issn: - 1088-467X publication_status: published publisher: IOS Press quality_controlled: '1' scopus_import: '1' status: public title: Combining pattern-based CRFs and weighted context-free grammars type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 26 year: '2022' ... --- _id: '7577' abstract: - lang: eng text: Weak convergence of inertial iterative method for solving variational inequalities is the focus of this paper. The cost function is assumed to be non-Lipschitz and monotone. We propose a projection-type method with inertial terms and give weak convergence analysis under appropriate conditions. Some test results are performed and compared with relevant methods in the literature to show the efficiency and advantages given by our proposed methods. acknowledgement: The project of the first author has received funding from the European Research Council (ERC) under the European Union's Seventh Framework Program (FP7 - 2007-2013) (Grant agreement No. 616160). article_processing_charge: No article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Olaniyi S. full_name: Iyiola, Olaniyi S. last_name: Iyiola citation: ama: Shehu Y, Iyiola OS. Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. 2022;101(1):192-216. doi:10.1080/00036811.2020.1736287 apa: Shehu, Y., & Iyiola, O. S. (2022). Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. Taylor & Francis. https://doi.org/10.1080/00036811.2020.1736287 chicago: Shehu, Yekini, and Olaniyi S. Iyiola. “Weak Convergence for Variational Inequalities with Inertial-Type Method.” Applicable Analysis. Taylor & Francis, 2022. https://doi.org/10.1080/00036811.2020.1736287. ieee: Y. Shehu and O. S. Iyiola, “Weak convergence for variational inequalities with inertial-type method,” Applicable Analysis, vol. 101, no. 1. Taylor & Francis, pp. 192–216, 2022. ista: Shehu Y, Iyiola OS. 2022. Weak convergence for variational inequalities with inertial-type method. Applicable Analysis. 101(1), 192–216. mla: Shehu, Yekini, and Olaniyi S. Iyiola. “Weak Convergence for Variational Inequalities with Inertial-Type Method.” Applicable Analysis, vol. 101, no. 1, Taylor & Francis, 2022, pp. 192–216, doi:10.1080/00036811.2020.1736287. short: Y. Shehu, O.S. Iyiola, Applicable Analysis 101 (2022) 192–216. date_created: 2020-03-09T07:06:52Z date_published: 2022-01-01T00:00:00Z date_updated: 2024-03-05T14:01:52Z day: '01' ddc: - '510' - '515' - '518' department: - _id: VlKo doi: 10.1080/00036811.2020.1736287 ec_funded: 1 external_id: arxiv: - '2101.08057' isi: - '000518364100001' file: - access_level: open_access checksum: 869efe8cb09505dfa6012f67d20db63d content_type: application/pdf creator: dernst date_created: 2020-10-12T10:42:54Z date_updated: 2021-03-16T23:30:06Z embargo: 2021-03-15 file_id: '8648' file_name: 2020_ApplicAnalysis_Shehu.pdf file_size: 4282586 relation: main_file file_date_updated: 2021-03-16T23:30:06Z has_accepted_license: '1' intvolume: ' 101' isi: 1 issue: '1' language: - iso: eng month: '01' oa: 1 oa_version: Submitted Version page: 192-216 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Applicable Analysis publication_identifier: eissn: - 1563-504X issn: - 0003-6811 publication_status: published publisher: Taylor & Francis quality_controlled: '1' scopus_import: '1' status: public title: Weak convergence for variational inequalities with inertial-type method type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 101 year: '2022' ... --- _id: '10072' abstract: - lang: eng text: The Lovász Local Lemma (LLL) is a powerful tool in probabilistic combinatorics which can be used to establish the existence of objects that satisfy certain properties. The breakthrough paper of Moser and Tardos and follow-up works revealed that the LLL has intimate connections with a class of stochastic local search algorithms for finding such desirable objects. In particular, it can be seen as a sufficient condition for this type of algorithms to converge fast. Besides conditions for existence of and fast convergence to desirable objects, one may naturally ask further questions regarding properties of these algorithms. For instance, "are they parallelizable?", "how many solutions can they output?", "what is the expected "weight" of a solution?", etc. These questions and more have been answered for a class of LLL-inspired algorithms called commutative. In this paper we introduce a new, very natural and more general notion of commutativity (essentially matrix commutativity) which allows us to show a number of new refined properties of LLL-inspired local search algorithms with significantly simpler proofs. acknowledgement: "Fotis Iliopoulos: This material is based upon work directly supported by the IAS Fund for Math and indirectly supported by the National Science Foundation Grant No. CCF-1900460. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This work is also supported by the National Science Foundation Grant No. CCF-1815328.\r\nVladimir Kolmogorov: Supported by the European Research Council under the European Unions Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no 616160." alternative_title: - LIPIcs article_number: '31' article_processing_charge: Yes author: - first_name: David G. full_name: Harris, David G. last_name: Harris - first_name: Fotis full_name: Iliopoulos, Fotis last_name: Iliopoulos - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Harris DG, Iliopoulos F, Kolmogorov V. A new notion of commutativity for the algorithmic Lovász Local Lemma. In: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. Vol 207. Schloss Dagstuhl - Leibniz Zentrum für Informatik; 2021. doi:10.4230/LIPIcs.APPROX/RANDOM.2021.31' apa: 'Harris, D. G., Iliopoulos, F., & Kolmogorov, V. (2021). A new notion of commutativity for the algorithmic Lovász Local Lemma. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (Vol. 207). Virtual: Schloss Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2021.31' chicago: Harris, David G., Fotis Iliopoulos, and Vladimir Kolmogorov. “A New Notion of Commutativity for the Algorithmic Lovász Local Lemma.” In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, Vol. 207. Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021. https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2021.31. ieee: D. G. Harris, F. Iliopoulos, and V. Kolmogorov, “A new notion of commutativity for the algorithmic Lovász Local Lemma,” in Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, Virtual, 2021, vol. 207. ista: 'Harris DG, Iliopoulos F, Kolmogorov V. 2021. A new notion of commutativity for the algorithmic Lovász Local Lemma. Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. APPROX/RANDOM: Approximation Algorithms for Combinatorial Optimization Problems/ Randomization and Computation, LIPIcs, vol. 207, 31.' mla: Harris, David G., et al. “A New Notion of Commutativity for the Algorithmic Lovász Local Lemma.” Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, vol. 207, 31, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021, doi:10.4230/LIPIcs.APPROX/RANDOM.2021.31. short: D.G. Harris, F. Iliopoulos, V. Kolmogorov, in:, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, Schloss Dagstuhl - Leibniz Zentrum für Informatik, 2021. conference: end_date: 2021-08-18 location: Virtual name: 'APPROX/RANDOM: Approximation Algorithms for Combinatorial Optimization Problems/ Randomization and Computation' start_date: 2021-08-16 date_created: 2021-10-03T22:01:22Z date_published: 2021-09-15T00:00:00Z date_updated: 2022-03-18T10:08:25Z day: '15' ddc: - '000' department: - _id: VlKo doi: 10.4230/LIPIcs.APPROX/RANDOM.2021.31 ec_funded: 1 external_id: arxiv: - '2008.05569' file: - access_level: open_access checksum: 9d2544d53aa5b01565c6891d97a4d765 content_type: application/pdf creator: cchlebak date_created: 2021-10-06T13:51:54Z date_updated: 2021-10-06T13:51:54Z file_id: '10098' file_name: 2021_LIPIcs_Harris.pdf file_size: 804472 relation: main_file success: 1 file_date_updated: 2021-10-06T13:51:54Z has_accepted_license: '1' intvolume: ' 207' language: - iso: eng month: '09' oa: 1 oa_version: Published Version project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques publication_identifier: isbn: - 978-3-9597-7207-5 issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz Zentrum für Informatik quality_controlled: '1' scopus_import: '1' status: public title: A new notion of commutativity for the algorithmic Lovász Local Lemma tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 207 year: '2021' ... --- _id: '10552' abstract: - lang: eng text: We study a class of convex-concave saddle-point problems of the form minxmaxy⟨Kx,y⟩+fP(x)−h∗(y) where K is a linear operator, fP is the sum of a convex function f with a Lipschitz-continuous gradient and the indicator function of a bounded convex polytope P, and h∗ is a convex (possibly nonsmooth) function. Such problem arises, for example, as a Lagrangian relaxation of various discrete optimization problems. Our main assumptions are the existence of an efficient linear minimization oracle (lmo) for fP and an efficient proximal map for h∗ which motivate the solution via a blend of proximal primal-dual algorithms and Frank-Wolfe algorithms. In case h∗ is the indicator function of a linear constraint and function f is quadratic, we show a O(1/n2) convergence rate on the dual objective, requiring O(nlogn) calls of lmo. If the problem comes from the constrained optimization problem minx∈Rd{fP(x)|Ax−b=0} then we additionally get bound O(1/n2) both on the primal gap and on the infeasibility gap. In the most general case, we show a O(1/n) convergence rate of the primal-dual gap again requiring O(nlogn) calls of lmo. To the best of our knowledge, this improves on the known convergence rates for the considered class of saddle-point problems. We show applications to labeling problems frequently appearing in machine learning and computer vision. acknowledgement: Vladimir Kolmogorov was supported by the European Research Council under the European Unions Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no 616160. Thomas Pock acknowledges support by an ERC grant HOMOVIS, no 640156. article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Thomas full_name: Pock, Thomas last_name: Pock citation: ama: 'Kolmogorov V, Pock T. One-sided Frank-Wolfe algorithms for saddle problems. In: 38th International Conference on Machine Learning. ; 2021.' apa: Kolmogorov, V., & Pock, T. (2021). One-sided Frank-Wolfe algorithms for saddle problems. In 38th International Conference on Machine Learning. Virtual. chicago: Kolmogorov, Vladimir, and Thomas Pock. “One-Sided Frank-Wolfe Algorithms for Saddle Problems.” In 38th International Conference on Machine Learning, 2021. ieee: V. Kolmogorov and T. Pock, “One-sided Frank-Wolfe algorithms for saddle problems,” in 38th International Conference on Machine Learning, Virtual, 2021. ista: 'Kolmogorov V, Pock T. 2021. One-sided Frank-Wolfe algorithms for saddle problems. 38th International Conference on Machine Learning. ICML: International Conference on Machine Learning.' mla: Kolmogorov, Vladimir, and Thomas Pock. “One-Sided Frank-Wolfe Algorithms for Saddle Problems.” 38th International Conference on Machine Learning, 2021. short: V. Kolmogorov, T. Pock, in:, 38th International Conference on Machine Learning, 2021. conference: end_date: 2021-07-24 location: Virtual name: 'ICML: International Conference on Machine Learning' start_date: 2021-07-18 date_created: 2021-12-16T12:41:20Z date_published: 2021-07-01T00:00:00Z date_updated: 2021-12-17T09:06:46Z day: '01' department: - _id: VlKo ec_funded: 1 external_id: arxiv: - '2101.12617' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2101.12617 month: '07' oa: 1 oa_version: Preprint project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: 38th International Conference on Machine Learning publication_status: published quality_controlled: '1' status: public title: One-sided Frank-Wolfe algorithms for saddle problems type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '9592' abstract: - lang: eng text: The convex grabbing game is a game where two players, Alice and Bob, alternate taking extremal points from the convex hull of a point set on the plane. Rational weights are given to the points. The goal of each player is to maximize the total weight over all points that they obtain. We restrict the setting to the case of binary weights. We show a construction of an arbitrarily large odd-sized point set that allows Bob to obtain almost 3/4 of the total weight. This construction answers a question asked by Matsumoto, Nakamigawa, and Sakuma in [Graphs and Combinatorics, 36/1 (2020)]. We also present an arbitrarily large even-sized point set where Bob can obtain the entirety of the total weight. Finally, we discuss conjectures about optimum moves in the convex grabbing game for both players in general. article_processing_charge: No author: - first_name: Martin full_name: Dvorak, Martin id: 40ED02A8-C8B4-11E9-A9C0-453BE6697425 last_name: Dvorak orcid: 0000-0001-5293-214X - first_name: Sara full_name: Nicholson, Sara last_name: Nicholson citation: ama: 'Dvorak M, Nicholson S. Massively winning configurations in the convex grabbing game on the plane. In: Proceedings of the 33rd Canadian Conference on Computational Geometry.' apa: Dvorak, M., & Nicholson, S. (n.d.). Massively winning configurations in the convex grabbing game on the plane. In Proceedings of the 33rd Canadian Conference on Computational Geometry. Halifax, NS, Canada. chicago: Dvorak, Martin, and Sara Nicholson. “Massively Winning Configurations in the Convex Grabbing Game on the Plane.” In Proceedings of the 33rd Canadian Conference on Computational Geometry, n.d. ieee: M. Dvorak and S. Nicholson, “Massively winning configurations in the convex grabbing game on the plane,” in Proceedings of the 33rd Canadian Conference on Computational Geometry, Halifax, NS, Canada. ista: 'Dvorak M, Nicholson S. Massively winning configurations in the convex grabbing game on the plane. Proceedings of the 33rd Canadian Conference on Computational Geometry. CCCG: Canadian Conference on Computational Geometry.' mla: Dvorak, Martin, and Sara Nicholson. “Massively Winning Configurations in the Convex Grabbing Game on the Plane.” Proceedings of the 33rd Canadian Conference on Computational Geometry. short: M. Dvorak, S. Nicholson, in:, Proceedings of the 33rd Canadian Conference on Computational Geometry, n.d. conference: end_date: 2021-08-12 location: Halifax, NS, Canada name: 'CCCG: Canadian Conference on Computational Geometry' start_date: 2021-08-10 date_created: 2021-06-22T15:57:11Z date_published: 2021-06-29T00:00:00Z date_updated: 2021-08-12T10:57:39Z day: '29' ddc: - '516' department: - _id: GradSch - _id: VlKo external_id: arxiv: - '2106.11247' file: - access_level: open_access checksum: 45accb1de9b7e0e4bb2fbfe5fd3e6239 content_type: application/pdf creator: mdvorak date_created: 2021-06-28T20:23:13Z date_updated: 2021-06-28T20:23:13Z file_id: '9616' file_name: Convex-Grabbing-Game_CCCG_proc_version.pdf file_size: 381306 relation: main_file success: 1 - access_level: open_access checksum: 9199cf18c65658553487458cc24d0ab2 content_type: application/pdf creator: kschuh date_created: 2021-08-12T10:57:21Z date_updated: 2021-08-12T10:57:21Z file_id: '9902' file_name: Convex-Grabbing-Game_FULL-VERSION.pdf file_size: 403645 relation: main_file success: 1 file_date_updated: 2021-08-12T10:57:21Z has_accepted_license: '1' keyword: - convex grabbing game - graph grabbing game - combinatorial game - convex geometry language: - iso: eng license: https://creativecommons.org/licenses/by-nd/4.0/ month: '06' oa: 1 oa_version: Submitted Version publication: Proceedings of the 33rd Canadian Conference on Computational Geometry publication_status: accepted quality_controlled: '1' status: public title: Massively winning configurations in the convex grabbing game on the plane tmp: image: /image/cc_by_nd.png legal_code_url: https://creativecommons.org/licenses/by-nd/4.0/legalcode name: Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) short: CC BY-ND (4.0) type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '10045' abstract: - lang: eng text: "Given a fixed finite metric space (V,μ), the {\\em minimum 0-extension problem}, denoted as 0-Ext[μ], is equivalent to the following optimization problem: minimize function of the form minx∈Vn∑ifi(xi)+∑ijcijμ(xi,xj) where cij,cvi are given nonnegative costs and fi:V→R are functions given by fi(xi)=∑v∈Vcviμ(xi,v). The computational complexity of 0-Ext[μ] has been recently established by Karzanov and by Hirai: if metric μ is {\\em orientable modular} then 0-Ext[μ] can be solved in polynomial time, otherwise 0-Ext[μ] is NP-hard. To prove the tractability part, Hirai developed a theory of discrete convex functions on orientable modular graphs generalizing several known classes of functions in discrete convex analysis, such as L♮-convex functions. We consider a more general version of the problem in which unary functions fi(xi) can additionally have terms of the form cuv;iμ(xi,{u,v}) for {u,v}∈F, where set F⊆(V2) is fixed. We extend the complexity classification above by providing an explicit condition on (μ,F) for the problem to be tractable. In order to prove the tractability part, we generalize Hirai's theory and define a larger class of discrete convex functions. It covers, in particular, another well-known class of functions, namely submodular functions on an integer lattice. Finally, we improve the complexity of Hirai's algorithm for solving 0-Ext on orientable modular graphs.\r\n" article_number: '2109.10203' article_processing_charge: No author: - first_name: Martin full_name: Dvorak, Martin id: 40ED02A8-C8B4-11E9-A9C0-453BE6697425 last_name: Dvorak orcid: 0000-0001-5293-214X - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Dvorak M, Kolmogorov V. Generalized minimum 0-extension problem and discrete convexity. arXiv. doi:10.48550/arXiv.2109.10203 apa: Dvorak, M., & Kolmogorov, V. (n.d.). Generalized minimum 0-extension problem and discrete convexity. arXiv. https://doi.org/10.48550/arXiv.2109.10203 chicago: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2109.10203. ieee: M. Dvorak and V. Kolmogorov, “Generalized minimum 0-extension problem and discrete convexity,” arXiv. . ista: Dvorak M, Kolmogorov V. Generalized minimum 0-extension problem and discrete convexity. arXiv, 2109.10203. mla: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” ArXiv, 2109.10203, doi:10.48550/arXiv.2109.10203. short: M. Dvorak, V. Kolmogorov, ArXiv (n.d.). date_created: 2021-09-27T10:48:23Z date_published: 2021-09-21T00:00:00Z date_updated: 2023-05-03T10:40:16Z day: '21' ddc: - '004' department: - _id: GradSch - _id: VlKo doi: 10.48550/arXiv.2109.10203 external_id: arxiv: - '2109.10203' file: - access_level: open_access checksum: e7e83065f7bc18b9c188bf93b5ca5db6 content_type: application/pdf creator: mdvorak date_created: 2021-09-27T10:54:51Z date_updated: 2021-09-27T10:54:51Z file_id: '10046' file_name: Generalized-0-Ext.pdf file_size: 603672 relation: main_file success: 1 file_date_updated: 2021-09-27T10:54:51Z has_accepted_license: '1' keyword: - minimum 0-extension problem - metric labeling problem - discrete metric spaces - metric extensions - computational complexity - valued constraint satisfaction problems - discrete convex analysis - L-convex functions language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.48550/arXiv.2109.10203' month: '09' oa: 1 oa_version: Preprint publication: arXiv publication_status: submitted status: public title: Generalized minimum 0-extension problem and discrete convexity type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '9469' abstract: - lang: eng text: In this paper, we consider reflected three-operator splitting methods for monotone inclusion problems in real Hilbert spaces. To do this, we first obtain weak convergence analysis and nonasymptotic O(1/n) convergence rate of the reflected Krasnosel'skiĭ-Mann iteration for finding a fixed point of nonexpansive mapping in real Hilbert spaces under some seemingly easy to implement conditions on the iterative parameters. We then apply our results to three-operator splitting for the monotone inclusion problem and consequently obtain the corresponding convergence analysis. Furthermore, we derive reflected primal-dual algorithms for highly structured monotone inclusion problems. Some numerical implementations are drawn from splitting methods to support the theoretical analysis. acknowledgement: The authors are grateful to the anonymous referees and the handling Editor for their insightful comments which have improved the earlier version of the manuscript greatly. The second author is grateful to the University of Hafr Al Batin. The last author has received funding from the European Research Council (ERC) under the European Union's Seventh Framework Program (FP7-2007-2013) (Grant agreement No. 616160). article_processing_charge: No article_type: original author: - first_name: Olaniyi S. full_name: Iyiola, Olaniyi S. last_name: Iyiola - first_name: Cyril D. full_name: Enyi, Cyril D. last_name: Enyi - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 citation: ama: Iyiola OS, Enyi CD, Shehu Y. Reflected three-operator splitting method for monotone inclusion problem. Optimization Methods and Software. 2021. doi:10.1080/10556788.2021.1924715 apa: Iyiola, O. S., Enyi, C. D., & Shehu, Y. (2021). Reflected three-operator splitting method for monotone inclusion problem. Optimization Methods and Software. Taylor and Francis. https://doi.org/10.1080/10556788.2021.1924715 chicago: Iyiola, Olaniyi S., Cyril D. Enyi, and Yekini Shehu. “Reflected Three-Operator Splitting Method for Monotone Inclusion Problem.” Optimization Methods and Software. Taylor and Francis, 2021. https://doi.org/10.1080/10556788.2021.1924715. ieee: O. S. Iyiola, C. D. Enyi, and Y. Shehu, “Reflected three-operator splitting method for monotone inclusion problem,” Optimization Methods and Software. Taylor and Francis, 2021. ista: Iyiola OS, Enyi CD, Shehu Y. 2021. Reflected three-operator splitting method for monotone inclusion problem. Optimization Methods and Software. mla: Iyiola, Olaniyi S., et al. “Reflected Three-Operator Splitting Method for Monotone Inclusion Problem.” Optimization Methods and Software, Taylor and Francis, 2021, doi:10.1080/10556788.2021.1924715. short: O.S. Iyiola, C.D. Enyi, Y. Shehu, Optimization Methods and Software (2021). date_created: 2021-06-06T22:01:30Z date_published: 2021-05-12T00:00:00Z date_updated: 2023-08-08T13:57:43Z day: '12' department: - _id: VlKo doi: 10.1080/10556788.2021.1924715 ec_funded: 1 external_id: isi: - '000650507600001' isi: 1 language: - iso: eng month: '05' oa_version: None project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Optimization Methods and Software publication_identifier: eissn: - 1029-4937 issn: - 1055-6788 publication_status: published publisher: Taylor and Francis quality_controlled: '1' scopus_import: '1' status: public title: Reflected three-operator splitting method for monotone inclusion problem type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 year: '2021' ... --- _id: '9234' abstract: - lang: eng text: In this paper, we present two new inertial projection-type methods for solving multivalued variational inequality problems in finite-dimensional spaces. We establish the convergence of the sequence generated by these methods when the multivalued mapping associated with the problem is only required to be locally bounded without any monotonicity assumption. Furthermore, the inertial techniques that we employ in this paper are quite different from the ones used in most papers. Moreover, based on the weaker assumptions on the inertial factor in our methods, we derive several special cases of our methods. Finally, we present some experimental results to illustrate the profits that we gain by introducing the inertial extrapolation steps. acknowledgement: 'The authors sincerely thank the Editor-in-Chief and anonymous referees for their careful reading, constructive comments and fruitful suggestions that help improve the manuscript. The research of the first author is supported by the National Research Foundation (NRF) South Africa (S& F-DSI/NRF Free Standing Postdoctoral Fellowship; Grant Number: 120784). The first author also acknowledges the financial support from DSI/NRF, South Africa Center of Excellence in Mathematical and Statistical Sciences (CoE-MaSS) Postdoctoral Fellowship. The second author has received funding from the European Research Council (ERC) under the European Union’s Seventh Framework Program (FP7 - 2007-2013) (Grant agreement No. 616160). Open Access funding provided by Institute of Science and Technology (IST Austria).' article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Chinedu full_name: Izuchukwu, Chinedu last_name: Izuchukwu - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 citation: ama: Izuchukwu C, Shehu Y. New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity. Networks and Spatial Economics. 2021;21(2):291-323. doi:10.1007/s11067-021-09517-w apa: Izuchukwu, C., & Shehu, Y. (2021). New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity. Networks and Spatial Economics. Springer Nature. https://doi.org/10.1007/s11067-021-09517-w chicago: Izuchukwu, Chinedu, and Yekini Shehu. “New Inertial Projection Methods for Solving Multivalued Variational Inequality Problems beyond Monotonicity.” Networks and Spatial Economics. Springer Nature, 2021. https://doi.org/10.1007/s11067-021-09517-w. ieee: C. Izuchukwu and Y. Shehu, “New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity,” Networks and Spatial Economics, vol. 21, no. 2. Springer Nature, pp. 291–323, 2021. ista: Izuchukwu C, Shehu Y. 2021. New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity. Networks and Spatial Economics. 21(2), 291–323. mla: Izuchukwu, Chinedu, and Yekini Shehu. “New Inertial Projection Methods for Solving Multivalued Variational Inequality Problems beyond Monotonicity.” Networks and Spatial Economics, vol. 21, no. 2, Springer Nature, 2021, pp. 291–323, doi:10.1007/s11067-021-09517-w. short: C. Izuchukwu, Y. Shehu, Networks and Spatial Economics 21 (2021) 291–323. date_created: 2021-03-10T12:18:47Z date_published: 2021-06-01T00:00:00Z date_updated: 2023-09-05T15:32:32Z day: '01' ddc: - '510' department: - _id: VlKo doi: 10.1007/s11067-021-09517-w ec_funded: 1 external_id: isi: - '000625002100001' file: - access_level: open_access checksum: 22b4253a2e5da843622a2df713784b4c content_type: application/pdf creator: kschuh date_created: 2021-08-11T12:44:16Z date_updated: 2021-08-11T12:44:16Z file_id: '9884' file_name: 2021_NetworksSpatialEconomics_Shehu.pdf file_size: 834964 relation: main_file success: 1 file_date_updated: 2021-08-11T12:44:16Z has_accepted_license: '1' intvolume: ' 21' isi: 1 issue: '2' keyword: - Computer Networks and Communications - Software - Artificial Intelligence language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: 291-323 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' - _id: B67AFEDC-15C9-11EA-A837-991A96BB2854 name: IST Austria Open Access Fund publication: Networks and Spatial Economics publication_identifier: eissn: - 1572-9427 issn: - 1566-113X publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 21 year: '2021' ... --- _id: '9227' abstract: - lang: eng text: In the multiway cut problem we are given a weighted undirected graph G=(V,E) and a set T⊆V of k terminals. The goal is to find a minimum weight set of edges E′⊆E with the property that by removing E′ from G all the terminals become disconnected. In this paper we present a simple local search approximation algorithm for the multiway cut problem with approximation ratio 2−2k . We present an experimental evaluation of the performance of our local search algorithm and show that it greatly outperforms the isolation heuristic of Dalhaus et al. and it has similar performance as the much more complex algorithms of Calinescu et al., Sharma and Vondrak, and Buchbinder et al. which have the currently best known approximation ratios for this problem. alternative_title: - LNCS article_processing_charge: No author: - first_name: Andrew full_name: Bloch-Hansen, Andrew last_name: Bloch-Hansen - first_name: Nasim full_name: Samei, Nasim id: C1531CAE-36E9-11EA-845F-33AA3DDC885E last_name: Samei - first_name: Roberto full_name: Solis-Oba, Roberto last_name: Solis-Oba citation: ama: 'Bloch-Hansen A, Samei N, Solis-Oba R. Experimental evaluation of a local search approximation algorithm for the multiway cut problem. In: Conference on Algorithms and Discrete Applied Mathematics. Vol 12601. Springer Nature; 2021:346-358. doi:10.1007/978-3-030-67899-9_28' apa: 'Bloch-Hansen, A., Samei, N., & Solis-Oba, R. (2021). Experimental evaluation of a local search approximation algorithm for the multiway cut problem. In Conference on Algorithms and Discrete Applied Mathematics (Vol. 12601, pp. 346–358). Rupnagar, India: Springer Nature. https://doi.org/10.1007/978-3-030-67899-9_28' chicago: Bloch-Hansen, Andrew, Nasim Samei, and Roberto Solis-Oba. “Experimental Evaluation of a Local Search Approximation Algorithm for the Multiway Cut Problem.” In Conference on Algorithms and Discrete Applied Mathematics, 12601:346–58. Springer Nature, 2021. https://doi.org/10.1007/978-3-030-67899-9_28. ieee: A. Bloch-Hansen, N. Samei, and R. Solis-Oba, “Experimental evaluation of a local search approximation algorithm for the multiway cut problem,” in Conference on Algorithms and Discrete Applied Mathematics, Rupnagar, India, 2021, vol. 12601, pp. 346–358. ista: 'Bloch-Hansen A, Samei N, Solis-Oba R. 2021. Experimental evaluation of a local search approximation algorithm for the multiway cut problem. Conference on Algorithms and Discrete Applied Mathematics. CALDAM: Conference on Algorithms and Discrete Applied Mathematics, LNCS, vol. 12601, 346–358.' mla: Bloch-Hansen, Andrew, et al. “Experimental Evaluation of a Local Search Approximation Algorithm for the Multiway Cut Problem.” Conference on Algorithms and Discrete Applied Mathematics, vol. 12601, Springer Nature, 2021, pp. 346–58, doi:10.1007/978-3-030-67899-9_28. short: A. Bloch-Hansen, N. Samei, R. Solis-Oba, in:, Conference on Algorithms and Discrete Applied Mathematics, Springer Nature, 2021, pp. 346–358. conference: end_date: 2021-02-13 location: Rupnagar, India name: 'CALDAM: Conference on Algorithms and Discrete Applied Mathematics' start_date: 2021-02-11 date_created: 2021-03-07T23:01:25Z date_published: 2021-01-28T00:00:00Z date_updated: 2023-10-10T09:29:08Z day: '28' department: - _id: VlKo doi: 10.1007/978-3-030-67899-9_28 intvolume: ' 12601' language: - iso: eng month: '01' oa_version: None page: 346-358 publication: Conference on Algorithms and Discrete Applied Mathematics publication_identifier: eissn: - 1611-3349 isbn: - '9783030678982' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Experimental evaluation of a local search approximation algorithm for the multiway cut problem type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 12601 year: '2021' ... --- _id: '8817' abstract: - lang: eng text: The paper introduces an inertial extragradient subgradient method with self-adaptive step sizes for solving equilibrium problems in real Hilbert spaces. Weak convergence of the proposed method is obtained under the condition that the bifunction is pseudomonotone and Lipchitz continuous. Linear convergence is also given when the bifunction is strongly pseudomonotone and Lipchitz continuous. Numerical implementations and comparisons with other related inertial methods are given using test problems including a real-world application to Nash–Cournot oligopolistic electricity market equilibrium model. acknowledgement: The authors are grateful to the two referees and the Associate Editor for their comments and suggestions which have improved the earlier version of the paper greatly. The project of Yekini Shehu has received funding from the European Research Council (ERC) under the European Union’s Seventh Framework Program (FP7 - 2007-2013) (Grant agreement No. 616160). article_processing_charge: No article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Olaniyi S. full_name: Iyiola, Olaniyi S. last_name: Iyiola - first_name: Duong Viet full_name: Thong, Duong Viet last_name: Thong - first_name: Nguyen Thi Cam full_name: Van, Nguyen Thi Cam last_name: Van citation: ama: Shehu Y, Iyiola OS, Thong DV, Van NTC. An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems. Mathematical Methods of Operations Research. 2021;93(2):213-242. doi:10.1007/s00186-020-00730-w apa: Shehu, Y., Iyiola, O. S., Thong, D. V., & Van, N. T. C. (2021). An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems. Mathematical Methods of Operations Research. Springer Nature. https://doi.org/10.1007/s00186-020-00730-w chicago: Shehu, Yekini, Olaniyi S. Iyiola, Duong Viet Thong, and Nguyen Thi Cam Van. “An Inertial Subgradient Extragradient Algorithm Extended to Pseudomonotone Equilibrium Problems.” Mathematical Methods of Operations Research. Springer Nature, 2021. https://doi.org/10.1007/s00186-020-00730-w. ieee: Y. Shehu, O. S. Iyiola, D. V. Thong, and N. T. C. Van, “An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems,” Mathematical Methods of Operations Research, vol. 93, no. 2. Springer Nature, pp. 213–242, 2021. ista: Shehu Y, Iyiola OS, Thong DV, Van NTC. 2021. An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems. Mathematical Methods of Operations Research. 93(2), 213–242. mla: Shehu, Yekini, et al. “An Inertial Subgradient Extragradient Algorithm Extended to Pseudomonotone Equilibrium Problems.” Mathematical Methods of Operations Research, vol. 93, no. 2, Springer Nature, 2021, pp. 213–42, doi:10.1007/s00186-020-00730-w. short: Y. Shehu, O.S. Iyiola, D.V. Thong, N.T.C. Van, Mathematical Methods of Operations Research 93 (2021) 213–242. date_created: 2020-11-29T23:01:18Z date_published: 2021-04-01T00:00:00Z date_updated: 2023-10-10T09:30:23Z day: '01' department: - _id: VlKo doi: 10.1007/s00186-020-00730-w ec_funded: 1 external_id: isi: - '000590497300001' intvolume: ' 93' isi: 1 issue: '2' language: - iso: eng month: '04' oa_version: None page: 213-242 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Mathematical Methods of Operations Research publication_identifier: eissn: - 1432-5217 issn: - 1432-2994 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 93 year: '2021' ... --- _id: '9315' abstract: - lang: eng text: We consider inertial iteration methods for Fermat–Weber location problem and primal–dual three-operator splitting in real Hilbert spaces. To do these, we first obtain weak convergence analysis and nonasymptotic O(1/n) convergence rate of the inertial Krasnoselskii–Mann iteration for fixed point of nonexpansive operators in infinite dimensional real Hilbert spaces under some seemingly easy to implement conditions on the iterative parameters. One of our contributions is that the convergence analysis and rate of convergence results are obtained using conditions which appear not complicated and restrictive as assumed in other previous related results in the literature. We then show that Fermat–Weber location problem and primal–dual three-operator splitting are special cases of fixed point problem of nonexpansive mapping and consequently obtain the convergence analysis of inertial iteration methods for Fermat–Weber location problem and primal–dual three-operator splitting in real Hilbert spaces. Some numerical implementations are drawn from primal–dual three-operator splitting to support the theoretical analysis. acknowledgement: The research of this author is supported by the Postdoctoral Fellowship from Institute of Science and Technology (IST), Austria. article_number: '75' article_processing_charge: No article_type: original author: - first_name: Olaniyi S. full_name: Iyiola, Olaniyi S. last_name: Iyiola - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 citation: ama: Iyiola OS, Shehu Y. New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications. Results in Mathematics. 2021;76(2). doi:10.1007/s00025-021-01381-x apa: Iyiola, O. S., & Shehu, Y. (2021). New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications. Results in Mathematics. Springer Nature. https://doi.org/10.1007/s00025-021-01381-x chicago: Iyiola, Olaniyi S., and Yekini Shehu. “New Convergence Results for Inertial Krasnoselskii–Mann Iterations in Hilbert Spaces with Applications.” Results in Mathematics. Springer Nature, 2021. https://doi.org/10.1007/s00025-021-01381-x. ieee: O. S. Iyiola and Y. Shehu, “New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications,” Results in Mathematics, vol. 76, no. 2. Springer Nature, 2021. ista: Iyiola OS, Shehu Y. 2021. New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications. Results in Mathematics. 76(2), 75. mla: Iyiola, Olaniyi S., and Yekini Shehu. “New Convergence Results for Inertial Krasnoselskii–Mann Iterations in Hilbert Spaces with Applications.” Results in Mathematics, vol. 76, no. 2, 75, Springer Nature, 2021, doi:10.1007/s00025-021-01381-x. short: O.S. Iyiola, Y. Shehu, Results in Mathematics 76 (2021). date_created: 2021-04-11T22:01:14Z date_published: 2021-03-25T00:00:00Z date_updated: 2023-10-10T09:47:33Z day: '25' department: - _id: VlKo doi: 10.1007/s00025-021-01381-x external_id: isi: - '000632917700001' intvolume: ' 76' isi: 1 issue: '2' language: - iso: eng month: '03' oa_version: None publication: Results in Mathematics publication_identifier: eissn: - 1420-9012 issn: - 1422-6383 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 76 year: '2021' ... --- _id: '9365' abstract: - lang: eng text: In this paper, we propose a new iterative method with alternated inertial step for solving split common null point problem in real Hilbert spaces. We obtain weak convergence of the proposed iterative algorithm. Furthermore, we introduce the notion of bounded linear regularity property for the split common null point problem and obtain the linear convergence property for the new algorithm under some mild assumptions. Finally, we provide some numerical examples to demonstrate the performance and efficiency of the proposed method. acknowledgement: The second author has received funding from the European Research Council (ERC) under the European Union's Seventh Framework Program (FP7-2007-2013) (Grant agreement No. 616160). article_processing_charge: No article_type: original author: - first_name: Ferdinard U. full_name: Ogbuisi, Ferdinard U. last_name: Ogbuisi - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Jen Chih full_name: Yao, Jen Chih last_name: Yao citation: ama: Ogbuisi FU, Shehu Y, Yao JC. Convergence analysis of new inertial method for the split common null point problem. Optimization. 2021. doi:10.1080/02331934.2021.1914035 apa: Ogbuisi, F. U., Shehu, Y., & Yao, J. C. (2021). Convergence analysis of new inertial method for the split common null point problem. Optimization. Taylor and Francis. https://doi.org/10.1080/02331934.2021.1914035 chicago: Ogbuisi, Ferdinard U., Yekini Shehu, and Jen Chih Yao. “Convergence Analysis of New Inertial Method for the Split Common Null Point Problem.” Optimization. Taylor and Francis, 2021. https://doi.org/10.1080/02331934.2021.1914035. ieee: F. U. Ogbuisi, Y. Shehu, and J. C. Yao, “Convergence analysis of new inertial method for the split common null point problem,” Optimization. Taylor and Francis, 2021. ista: Ogbuisi FU, Shehu Y, Yao JC. 2021. Convergence analysis of new inertial method for the split common null point problem. Optimization. mla: Ogbuisi, Ferdinard U., et al. “Convergence Analysis of New Inertial Method for the Split Common Null Point Problem.” Optimization, Taylor and Francis, 2021, doi:10.1080/02331934.2021.1914035. short: F.U. Ogbuisi, Y. Shehu, J.C. Yao, Optimization (2021). date_created: 2021-05-02T22:01:29Z date_published: 2021-04-14T00:00:00Z date_updated: 2023-10-10T09:48:41Z day: '14' department: - _id: VlKo doi: 10.1080/02331934.2021.1914035 ec_funded: 1 external_id: isi: - '000640109300001' isi: 1 language: - iso: eng month: '04' oa_version: None project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Optimization publication_identifier: eissn: - 1029-4945 issn: - 0233-1934 publication_status: published publisher: Taylor and Francis quality_controlled: '1' scopus_import: '1' status: public title: Convergence analysis of new inertial method for the split common null point problem type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '8196' abstract: - lang: eng text: This paper aims to obtain a strong convergence result for a Douglas–Rachford splitting method with inertial extrapolation step for finding a zero of the sum of two set-valued maximal monotone operators without any further assumption of uniform monotonicity on any of the involved maximal monotone operators. Furthermore, our proposed method is easy to implement and the inertial factor in our proposed method is a natural choice. Our method of proof is of independent interest. Finally, some numerical implementations are given to confirm the theoretical analysis. acknowledgement: Open access funding provided by Institute of Science and Technology (IST Austria). The project of Yekini Shehu has received funding from the European Research Council (ERC) under the European Union’s Seventh Framework Program (FP7—2007–2013) (Grant Agreement No. 616160). The authors are grateful to the anonymous referees and the handling Editor for their comments and suggestions which have improved the earlier version of the manuscript greatly. article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Qiao-Li full_name: Dong, Qiao-Li last_name: Dong - first_name: Lu-Lu full_name: Liu, Lu-Lu last_name: Liu - first_name: Jen-Chih full_name: Yao, Jen-Chih last_name: Yao citation: ama: Shehu Y, Dong Q-L, Liu L-L, Yao J-C. New strong convergence method for the sum of two maximal monotone operators. Optimization and Engineering. 2021;22:2627-2653. doi:10.1007/s11081-020-09544-5 apa: Shehu, Y., Dong, Q.-L., Liu, L.-L., & Yao, J.-C. (2021). New strong convergence method for the sum of two maximal monotone operators. Optimization and Engineering. Springer Nature. https://doi.org/10.1007/s11081-020-09544-5 chicago: Shehu, Yekini, Qiao-Li Dong, Lu-Lu Liu, and Jen-Chih Yao. “New Strong Convergence Method for the Sum of Two Maximal Monotone Operators.” Optimization and Engineering. Springer Nature, 2021. https://doi.org/10.1007/s11081-020-09544-5. ieee: Y. Shehu, Q.-L. Dong, L.-L. Liu, and J.-C. Yao, “New strong convergence method for the sum of two maximal monotone operators,” Optimization and Engineering, vol. 22. Springer Nature, pp. 2627–2653, 2021. ista: Shehu Y, Dong Q-L, Liu L-L, Yao J-C. 2021. New strong convergence method for the sum of two maximal monotone operators. Optimization and Engineering. 22, 2627–2653. mla: Shehu, Yekini, et al. “New Strong Convergence Method for the Sum of Two Maximal Monotone Operators.” Optimization and Engineering, vol. 22, Springer Nature, 2021, pp. 2627–53, doi:10.1007/s11081-020-09544-5. short: Y. Shehu, Q.-L. Dong, L.-L. Liu, J.-C. Yao, Optimization and Engineering 22 (2021) 2627–2653. date_created: 2020-08-03T14:29:57Z date_published: 2021-02-25T00:00:00Z date_updated: 2024-03-07T14:39:29Z day: '25' ddc: - '510' department: - _id: VlKo doi: 10.1007/s11081-020-09544-5 ec_funded: 1 external_id: isi: - '000559345400001' file: - access_level: open_access content_type: application/pdf creator: dernst date_created: 2020-08-03T15:24:39Z date_updated: 2020-08-03T15:24:39Z file_id: '8197' file_name: 2020_OptimizationEngineering_Shehu.pdf file_size: 2137860 relation: main_file success: 1 file_date_updated: 2020-08-03T15:24:39Z has_accepted_license: '1' intvolume: ' 22' isi: 1 language: - iso: eng month: '02' oa: 1 oa_version: Published Version page: 2627-2653 project: - _id: B67AFEDC-15C9-11EA-A837-991A96BB2854 name: IST Austria Open Access Fund - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Optimization and Engineering publication_identifier: eissn: - 1573-2924 issn: - 1389-4420 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: New strong convergence method for the sum of two maximal monotone operators tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 22 year: '2021' ... --- _id: '7925' abstract: - lang: eng text: In this paper, we introduce a relaxed CQ method with alternated inertial step for solving split feasibility problems. We give convergence of the sequence generated by our method under some suitable assumptions. Some numerical implementations from sparse signal and image deblurring are reported to show the efficiency of our method. acknowledgement: Open access funding provided by Institute of Science and Technology (IST Austria). The authors are grateful to the referees for their insightful comments which have improved the earlier version of the manuscript greatly. The first author has received funding from the European Research Council (ERC) under the European Union’s Seventh Framework Program (FP7-2007-2013) (Grant agreement No. 616160). article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Aviv full_name: Gibali, Aviv last_name: Gibali citation: ama: Shehu Y, Gibali A. New inertial relaxed method for solving split feasibilities. Optimization Letters. 2021;15:2109-2126. doi:10.1007/s11590-020-01603-1 apa: Shehu, Y., & Gibali, A. (2021). New inertial relaxed method for solving split feasibilities. Optimization Letters. Springer Nature. https://doi.org/10.1007/s11590-020-01603-1 chicago: Shehu, Yekini, and Aviv Gibali. “New Inertial Relaxed Method for Solving Split Feasibilities.” Optimization Letters. Springer Nature, 2021. https://doi.org/10.1007/s11590-020-01603-1. ieee: Y. Shehu and A. Gibali, “New inertial relaxed method for solving split feasibilities,” Optimization Letters, vol. 15. Springer Nature, pp. 2109–2126, 2021. ista: Shehu Y, Gibali A. 2021. New inertial relaxed method for solving split feasibilities. Optimization Letters. 15, 2109–2126. mla: Shehu, Yekini, and Aviv Gibali. “New Inertial Relaxed Method for Solving Split Feasibilities.” Optimization Letters, vol. 15, Springer Nature, 2021, pp. 2109–26, doi:10.1007/s11590-020-01603-1. short: Y. Shehu, A. Gibali, Optimization Letters 15 (2021) 2109–2126. date_created: 2020-06-04T11:28:33Z date_published: 2021-09-01T00:00:00Z date_updated: 2024-03-07T15:00:43Z day: '01' ddc: - '510' department: - _id: VlKo doi: 10.1007/s11590-020-01603-1 ec_funded: 1 external_id: isi: - '000537342300001' file: - access_level: open_access checksum: 63c5f31cd04626152a19f97a2476281b content_type: application/pdf creator: kschuh date_created: 2024-03-07T14:58:51Z date_updated: 2024-03-07T14:58:51Z file_id: '15089' file_name: 2021_OptimizationLetters_Shehu.pdf file_size: 2148882 relation: main_file success: 1 file_date_updated: 2024-03-07T14:58:51Z has_accepted_license: '1' intvolume: ' 15' isi: 1 language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: 2109-2126 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' - _id: B67AFEDC-15C9-11EA-A837-991A96BB2854 name: IST Austria Open Access Fund publication: Optimization Letters publication_identifier: eissn: - 1862-4480 issn: - 1862-4472 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: New inertial relaxed method for solving split feasibilities tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 15 year: '2021' ... --- _id: '6593' abstract: - lang: eng text: 'We consider the monotone variational inequality problem in a Hilbert space and describe a projection-type method with inertial terms under the following properties: (a) The method generates a strongly convergent iteration sequence; (b) The method requires, at each iteration, only one projection onto the feasible set and two evaluations of the operator; (c) The method is designed for variational inequality for which the underline operator is monotone and uniformly continuous; (d) The method includes an inertial term. The latter is also shown to speed up the convergence in our numerical results. A comparison with some related methods is given and indicates that the new method is promising.' acknowledgement: The research of this author is supported by the ERC grant at the IST. article_processing_charge: No article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Xiao-Huan full_name: Li, Xiao-Huan last_name: Li - first_name: Qiao-Li full_name: Dong, Qiao-Li last_name: Dong citation: ama: Shehu Y, Li X-H, Dong Q-L. An efficient projection-type method for monotone variational inequalities in Hilbert spaces. Numerical Algorithms. 2020;84:365-388. doi:10.1007/s11075-019-00758-y apa: Shehu, Y., Li, X.-H., & Dong, Q.-L. (2020). An efficient projection-type method for monotone variational inequalities in Hilbert spaces. Numerical Algorithms. Springer Nature. https://doi.org/10.1007/s11075-019-00758-y chicago: Shehu, Yekini, Xiao-Huan Li, and Qiao-Li Dong. “An Efficient Projection-Type Method for Monotone Variational Inequalities in Hilbert Spaces.” Numerical Algorithms. Springer Nature, 2020. https://doi.org/10.1007/s11075-019-00758-y. ieee: Y. Shehu, X.-H. Li, and Q.-L. Dong, “An efficient projection-type method for monotone variational inequalities in Hilbert spaces,” Numerical Algorithms, vol. 84. Springer Nature, pp. 365–388, 2020. ista: Shehu Y, Li X-H, Dong Q-L. 2020. An efficient projection-type method for monotone variational inequalities in Hilbert spaces. Numerical Algorithms. 84, 365–388. mla: Shehu, Yekini, et al. “An Efficient Projection-Type Method for Monotone Variational Inequalities in Hilbert Spaces.” Numerical Algorithms, vol. 84, Springer Nature, 2020, pp. 365–88, doi:10.1007/s11075-019-00758-y. short: Y. Shehu, X.-H. Li, Q.-L. Dong, Numerical Algorithms 84 (2020) 365–388. date_created: 2019-06-27T20:09:33Z date_published: 2020-05-01T00:00:00Z date_updated: 2023-08-17T13:51:18Z day: '01' ddc: - '000' department: - _id: VlKo doi: 10.1007/s11075-019-00758-y ec_funded: 1 external_id: isi: - '000528979000015' file: - access_level: open_access checksum: bb1a1eb3ebb2df380863d0db594673ba content_type: application/pdf creator: kschuh date_created: 2019-10-01T13:14:10Z date_updated: 2020-07-14T12:47:34Z file_id: '6927' file_name: ExtragradientMethodPaper.pdf file_size: 359654 relation: main_file file_date_updated: 2020-07-14T12:47:34Z has_accepted_license: '1' intvolume: ' 84' isi: 1 language: - iso: eng month: '05' oa: 1 oa_version: Submitted Version page: 365-388 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Numerical Algorithms publication_identifier: eissn: - 1572-9265 issn: - 1017-1398 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: An efficient projection-type method for monotone variational inequalities in Hilbert spaces type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 84 year: '2020' ... --- _id: '8077' abstract: - lang: eng text: The projection methods with vanilla inertial extrapolation step for variational inequalities have been of interest to many authors recently due to the improved convergence speed contributed by the presence of inertial extrapolation step. However, it is discovered that these projection methods with inertial steps lose the Fejér monotonicity of the iterates with respect to the solution, which is being enjoyed by their corresponding non-inertial projection methods for variational inequalities. This lack of Fejér monotonicity makes projection methods with vanilla inertial extrapolation step for variational inequalities not to converge faster than their corresponding non-inertial projection methods at times. Also, it has recently been proved that the projection methods with vanilla inertial extrapolation step may provide convergence rates that are worse than the classical projected gradient methods for strongly convex functions. In this paper, we introduce projection methods with alternated inertial extrapolation step for solving variational inequalities. We show that the sequence of iterates generated by our methods converges weakly to a solution of the variational inequality under some appropriate conditions. The Fejér monotonicity of even subsequence is recovered in these methods and linear rate of convergence is obtained. The numerical implementations of our methods compared with some other inertial projection methods show that our method is more efficient and outperforms some of these inertial projection methods. acknowledgement: The authors are grateful to the two anonymous referees for their insightful comments and suggestions which have improved the earlier version of the manuscript greatly. The first author has received funding from the European Research Council (ERC) under the European Union Seventh Framework Programme (FP7 - 2007-2013) (Grant agreement No. 616160). article_processing_charge: No article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Olaniyi S. full_name: Iyiola, Olaniyi S. last_name: Iyiola citation: ama: 'Shehu Y, Iyiola OS. Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence. Applied Numerical Mathematics. 2020;157:315-337. doi:10.1016/j.apnum.2020.06.009' apa: 'Shehu, Y., & Iyiola, O. S. (2020). Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence. Applied Numerical Mathematics. Elsevier. https://doi.org/10.1016/j.apnum.2020.06.009' chicago: 'Shehu, Yekini, and Olaniyi S. Iyiola. “Projection Methods with Alternating Inertial Steps for Variational Inequalities: Weak and Linear Convergence.” Applied Numerical Mathematics. Elsevier, 2020. https://doi.org/10.1016/j.apnum.2020.06.009.' ieee: 'Y. Shehu and O. S. Iyiola, “Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence,” Applied Numerical Mathematics, vol. 157. Elsevier, pp. 315–337, 2020.' ista: 'Shehu Y, Iyiola OS. 2020. Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence. Applied Numerical Mathematics. 157, 315–337.' mla: 'Shehu, Yekini, and Olaniyi S. Iyiola. “Projection Methods with Alternating Inertial Steps for Variational Inequalities: Weak and Linear Convergence.” Applied Numerical Mathematics, vol. 157, Elsevier, 2020, pp. 315–37, doi:10.1016/j.apnum.2020.06.009.' short: Y. Shehu, O.S. Iyiola, Applied Numerical Mathematics 157 (2020) 315–337. date_created: 2020-07-02T09:02:33Z date_published: 2020-11-01T00:00:00Z date_updated: 2023-08-22T07:50:43Z day: '01' ddc: - '510' department: - _id: VlKo doi: 10.1016/j.apnum.2020.06.009 ec_funded: 1 external_id: isi: - '000564648400018' file: - access_level: open_access checksum: 87d81324a62c82baa925c009dfcb0200 content_type: application/pdf creator: dernst date_created: 2020-07-02T09:08:59Z date_updated: 2020-07-14T12:48:09Z file_id: '8078' file_name: 2020_AppliedNumericalMath_Shehu.pdf file_size: 2874203 relation: main_file file_date_updated: 2020-07-14T12:48:09Z has_accepted_license: '1' intvolume: ' 157' isi: 1 language: - iso: eng month: '11' oa: 1 oa_version: Submitted Version page: 315-337 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Applied Numerical Mathematics publication_identifier: issn: - 0168-9274 publication_status: published publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: 'Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence' type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 157 year: '2020' ... --- _id: '7161' abstract: - lang: eng text: In this paper, we introduce an inertial projection-type method with different updating strategies for solving quasi-variational inequalities with strongly monotone and Lipschitz continuous operators in real Hilbert spaces. Under standard assumptions, we establish different strong convergence results for the proposed algorithm. Primary numerical experiments demonstrate the potential applicability of our scheme compared with some related methods in the literature. acknowledgement: We are grateful to the anonymous referees and editor whose insightful comments helped to considerably improve an earlier version of this paper. The research of the first author is supported by an ERC Grant from the Institute of Science and Technology (IST). article_processing_charge: No article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Aviv full_name: Gibali, Aviv last_name: Gibali - first_name: Simone full_name: Sagratella, Simone last_name: Sagratella citation: ama: Shehu Y, Gibali A, Sagratella S. Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces. Journal of Optimization Theory and Applications. 2020;184:877–894. doi:10.1007/s10957-019-01616-6 apa: Shehu, Y., Gibali, A., & Sagratella, S. (2020). Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces. Journal of Optimization Theory and Applications. Springer Nature. https://doi.org/10.1007/s10957-019-01616-6 chicago: Shehu, Yekini, Aviv Gibali, and Simone Sagratella. “Inertial Projection-Type Methods for Solving Quasi-Variational Inequalities in Real Hilbert Spaces.” Journal of Optimization Theory and Applications. Springer Nature, 2020. https://doi.org/10.1007/s10957-019-01616-6. ieee: Y. Shehu, A. Gibali, and S. Sagratella, “Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces,” Journal of Optimization Theory and Applications, vol. 184. Springer Nature, pp. 877–894, 2020. ista: Shehu Y, Gibali A, Sagratella S. 2020. Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces. Journal of Optimization Theory and Applications. 184, 877–894. mla: Shehu, Yekini, et al. “Inertial Projection-Type Methods for Solving Quasi-Variational Inequalities in Real Hilbert Spaces.” Journal of Optimization Theory and Applications, vol. 184, Springer Nature, 2020, pp. 877–894, doi:10.1007/s10957-019-01616-6. short: Y. Shehu, A. Gibali, S. Sagratella, Journal of Optimization Theory and Applications 184 (2020) 877–894. date_created: 2019-12-09T21:33:44Z date_published: 2020-03-01T00:00:00Z date_updated: 2023-09-06T11:27:15Z day: '01' ddc: - '518' - '510' - '515' department: - _id: VlKo doi: 10.1007/s10957-019-01616-6 ec_funded: 1 external_id: isi: - '000511805200009' file: - access_level: open_access checksum: 9f6dc6c6bf2b48cb3a2091a9ed5feaf2 content_type: application/pdf creator: dernst date_created: 2020-10-12T10:40:27Z date_updated: 2021-03-16T23:30:04Z embargo: 2021-03-15 file_id: '8647' file_name: 2020_JourOptimizationTheoryApplic_Shehu.pdf file_size: 332641 relation: main_file file_date_updated: 2021-03-16T23:30:04Z has_accepted_license: '1' intvolume: ' 184' isi: 1 language: - iso: eng month: '03' oa: 1 oa_version: Submitted Version page: 877–894 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Journal of Optimization Theory and Applications publication_identifier: eissn: - 1573-2878 issn: - 0022-3239 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 184 year: '2020' ... --- _id: '6725' abstract: - lang: eng text: "A Valued Constraint Satisfaction Problem (VCSP) provides a common framework that can express a wide range of discrete optimization problems. A VCSP instance is given by a finite set of variables, a finite domain of labels, and an objective function to be minimized. This function is represented as a sum of terms where each term depends on a subset of the variables. To obtain different classes of optimization problems, one can restrict all terms to come from a fixed set Γ of cost functions, called a language. \r\nRecent breakthrough results have established a complete complexity classification of such classes with respect to language Γ: if all cost functions in Γ satisfy a certain algebraic condition then all Γ-instances can be solved in polynomial time, otherwise the problem is NP-hard. Unfortunately, testing this condition for a given language Γ is known to be NP-hard. We thus study exponential algorithms for this meta-problem. We show that the tractability condition of a finite-valued language Γ can be tested in O(3‾√3|D|⋅poly(size(Γ))) time, where D is the domain of Γ and poly(⋅) is some fixed polynomial. We also obtain a matching lower bound under the Strong Exponential Time Hypothesis (SETH). More precisely, we prove that for any constant δ<1 there is no O(3‾√3δ|D|) algorithm, assuming that SETH holds." alternative_title: - LIPIcs author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Kolmogorov V. Testing the complexity of a valued CSP language. In: 46th International Colloquium on Automata, Languages and Programming. Vol 132. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2019:77:1-77:12. doi:10.4230/LIPICS.ICALP.2019.77' apa: 'Kolmogorov, V. (2019). Testing the complexity of a valued CSP language. In 46th International Colloquium on Automata, Languages and Programming (Vol. 132, p. 77:1-77:12). Patras, Greece: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPICS.ICALP.2019.77' chicago: Kolmogorov, Vladimir. “Testing the Complexity of a Valued CSP Language.” In 46th International Colloquium on Automata, Languages and Programming, 132:77:1-77:12. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. https://doi.org/10.4230/LIPICS.ICALP.2019.77. ieee: V. Kolmogorov, “Testing the complexity of a valued CSP language,” in 46th International Colloquium on Automata, Languages and Programming, Patras, Greece, 2019, vol. 132, p. 77:1-77:12. ista: 'Kolmogorov V. 2019. Testing the complexity of a valued CSP language. 46th International Colloquium on Automata, Languages and Programming. ICALP 2019: International Colloquim on Automata, Languages and Programming, LIPIcs, vol. 132, 77:1-77:12.' mla: Kolmogorov, Vladimir. “Testing the Complexity of a Valued CSP Language.” 46th International Colloquium on Automata, Languages and Programming, vol. 132, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019, p. 77:1-77:12, doi:10.4230/LIPICS.ICALP.2019.77. short: V. Kolmogorov, in:, 46th International Colloquium on Automata, Languages and Programming, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019, p. 77:1-77:12. conference: end_date: 2019-07-12 location: Patras, Greece name: 'ICALP 2019: International Colloquim on Automata, Languages and Programming' start_date: 2019-07-08 date_created: 2019-07-29T12:23:29Z date_published: 2019-07-01T00:00:00Z date_updated: 2021-01-12T08:08:40Z day: '01' ddc: - '000' department: - _id: VlKo doi: 10.4230/LIPICS.ICALP.2019.77 ec_funded: 1 external_id: arxiv: - '1803.02289' file: - access_level: open_access checksum: f5ebee8eec6ae09e30365578ee63a492 content_type: application/pdf creator: dernst date_created: 2019-07-31T07:01:45Z date_updated: 2020-07-14T12:47:38Z file_id: '6738' file_name: 2019_LIPICS_Kolmogorov.pdf file_size: 575475 relation: main_file file_date_updated: 2020-07-14T12:47:38Z has_accepted_license: '1' intvolume: ' 132' language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: 77:1-77:12 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: 46th International Colloquium on Automata, Languages and Programming publication_identifier: isbn: - 978-3-95977-109-2 issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: 1 status: public title: Testing the complexity of a valued CSP language tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 132 year: '2019' ... --- _id: '6596' abstract: - lang: eng text: It is well known that many problems in image recovery, signal processing, and machine learning can be modeled as finding zeros of the sum of maximal monotone and Lipschitz continuous monotone operators. Many papers have studied forward-backward splitting methods for finding zeros of the sum of two monotone operators in Hilbert spaces. Most of the proposed splitting methods in the literature have been proposed for the sum of maximal monotone and inverse-strongly monotone operators in Hilbert spaces. In this paper, we consider splitting methods for finding zeros of the sum of maximal monotone operators and Lipschitz continuous monotone operators in Banach spaces. We obtain weak and strong convergence results for the zeros of the sum of maximal monotone and Lipschitz continuous monotone operators in Banach spaces. Many already studied problems in the literature can be considered as special cases of this paper. article_number: '138' article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 citation: ama: Shehu Y. Convergence results of forward-backward algorithms for sum of monotone operators in Banach spaces. Results in Mathematics. 2019;74(4). doi:10.1007/s00025-019-1061-4 apa: Shehu, Y. (2019). Convergence results of forward-backward algorithms for sum of monotone operators in Banach spaces. Results in Mathematics. Springer. https://doi.org/10.1007/s00025-019-1061-4 chicago: Shehu, Yekini. “Convergence Results of Forward-Backward Algorithms for Sum of Monotone Operators in Banach Spaces.” Results in Mathematics. Springer, 2019. https://doi.org/10.1007/s00025-019-1061-4. ieee: Y. Shehu, “Convergence results of forward-backward algorithms for sum of monotone operators in Banach spaces,” Results in Mathematics, vol. 74, no. 4. Springer, 2019. ista: Shehu Y. 2019. Convergence results of forward-backward algorithms for sum of monotone operators in Banach spaces. Results in Mathematics. 74(4), 138. mla: Shehu, Yekini. “Convergence Results of Forward-Backward Algorithms for Sum of Monotone Operators in Banach Spaces.” Results in Mathematics, vol. 74, no. 4, 138, Springer, 2019, doi:10.1007/s00025-019-1061-4. short: Y. Shehu, Results in Mathematics 74 (2019). date_created: 2019-06-29T10:11:30Z date_published: 2019-12-01T00:00:00Z date_updated: 2023-08-28T12:26:22Z day: '01' ddc: - '000' department: - _id: VlKo doi: 10.1007/s00025-019-1061-4 ec_funded: 1 external_id: arxiv: - '2101.09068' isi: - '000473237500002' file: - access_level: open_access checksum: c6d18cb1e16fc0c36a0e0f30b4ebbc2d content_type: application/pdf creator: kschuh date_created: 2019-07-03T15:20:40Z date_updated: 2020-07-14T12:47:34Z file_id: '6605' file_name: Springer_2019_Shehu.pdf file_size: 466942 relation: main_file file_date_updated: 2020-07-14T12:47:34Z has_accepted_license: '1' intvolume: ' 74' isi: 1 issue: '4' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' - _id: B67AFEDC-15C9-11EA-A837-991A96BB2854 name: IST Austria Open Access Fund publication: Results in Mathematics publication_identifier: eissn: - 1420-9012 issn: - 1422-6383 publication_status: published publisher: Springer quality_controlled: '1' scopus_import: '1' status: public title: Convergence results of forward-backward algorithms for sum of monotone operators in Banach spaces tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 74 year: '2019' ... --- _id: '7000' abstract: - lang: eng text: The main contributions of this paper are the proposition and the convergence analysis of a class of inertial projection-type algorithm for solving variational inequality problems in real Hilbert spaces where the underline operator is monotone and uniformly continuous. We carry out a unified analysis of the proposed method under very mild assumptions. In particular, weak convergence of the generated sequence is established and nonasymptotic O(1 / n) rate of convergence is established, where n denotes the iteration counter. We also present some experimental results to illustrate the profits gained by introducing the inertial extrapolation steps. article_number: '161' article_processing_charge: No article_type: original author: - first_name: Yekini full_name: Shehu, Yekini id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87 last_name: Shehu orcid: 0000-0001-9224-7139 - first_name: Olaniyi S. full_name: Iyiola, Olaniyi S. last_name: Iyiola - first_name: Xiao-Huan full_name: Li, Xiao-Huan last_name: Li - first_name: Qiao-Li full_name: Dong, Qiao-Li last_name: Dong citation: ama: Shehu Y, Iyiola OS, Li X-H, Dong Q-L. Convergence analysis of projection method for variational inequalities. Computational and Applied Mathematics. 2019;38(4). doi:10.1007/s40314-019-0955-9 apa: Shehu, Y., Iyiola, O. S., Li, X.-H., & Dong, Q.-L. (2019). Convergence analysis of projection method for variational inequalities. Computational and Applied Mathematics. Springer Nature. https://doi.org/10.1007/s40314-019-0955-9 chicago: Shehu, Yekini, Olaniyi S. Iyiola, Xiao-Huan Li, and Qiao-Li Dong. “Convergence Analysis of Projection Method for Variational Inequalities.” Computational and Applied Mathematics. Springer Nature, 2019. https://doi.org/10.1007/s40314-019-0955-9. ieee: Y. Shehu, O. S. Iyiola, X.-H. Li, and Q.-L. Dong, “Convergence analysis of projection method for variational inequalities,” Computational and Applied Mathematics, vol. 38, no. 4. Springer Nature, 2019. ista: Shehu Y, Iyiola OS, Li X-H, Dong Q-L. 2019. Convergence analysis of projection method for variational inequalities. Computational and Applied Mathematics. 38(4), 161. mla: Shehu, Yekini, et al. “Convergence Analysis of Projection Method for Variational Inequalities.” Computational and Applied Mathematics, vol. 38, no. 4, 161, Springer Nature, 2019, doi:10.1007/s40314-019-0955-9. short: Y. Shehu, O.S. Iyiola, X.-H. Li, Q.-L. Dong, Computational and Applied Mathematics 38 (2019). date_created: 2019-11-12T12:41:44Z date_published: 2019-12-01T00:00:00Z date_updated: 2023-08-30T07:20:32Z day: '01' ddc: - '510' - '515' - '518' department: - _id: VlKo doi: 10.1007/s40314-019-0955-9 ec_funded: 1 external_id: arxiv: - '2101.09081' isi: - '000488973100005' has_accepted_license: '1' intvolume: ' 38' isi: 1 issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1007/s40314-019-0955-9 month: '12' oa: 1 oa_version: Published Version project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Computational and Applied Mathematics publication_identifier: eissn: - 1807-0302 issn: - 2238-3603 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Convergence analysis of projection method for variational inequalities type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 38 year: '2019' ... --- _id: '7412' abstract: - lang: eng text: We develop a framework for the rigorous analysis of focused stochastic local search algorithms. These algorithms search a state space by repeatedly selecting some constraint that is violated in the current state and moving to a random nearby state that addresses the violation, while (we hope) not introducing many new violations. An important class of focused local search algorithms with provable performance guarantees has recently arisen from algorithmizations of the Lovász local lemma (LLL), a nonconstructive tool for proving the existence of satisfying states by introducing a background measure on the state space. While powerful, the state transitions of algorithms in this class must be, in a precise sense, perfectly compatible with the background measure. In many applications this is a very restrictive requirement, and one needs to step outside the class. Here we introduce the notion of measure distortion and develop a framework for analyzing arbitrary focused stochastic local search algorithms, recovering LLL algorithmizations as the special case of no distortion. Our framework takes as input an arbitrary algorithm of such type and an arbitrary probability measure and shows how to use the measure as a yardstick of algorithmic progress, even for algorithms designed independently of the measure. article_processing_charge: No article_type: original author: - first_name: Dimitris full_name: Achlioptas, Dimitris last_name: Achlioptas - first_name: Fotis full_name: Iliopoulos, Fotis last_name: Iliopoulos - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Achlioptas D, Iliopoulos F, Kolmogorov V. A local lemma for focused stochastical algorithms. SIAM Journal on Computing. 2019;48(5):1583-1602. doi:10.1137/16m109332x apa: Achlioptas, D., Iliopoulos, F., & Kolmogorov, V. (2019). A local lemma for focused stochastical algorithms. SIAM Journal on Computing. SIAM. https://doi.org/10.1137/16m109332x chicago: Achlioptas, Dimitris, Fotis Iliopoulos, and Vladimir Kolmogorov. “A Local Lemma for Focused Stochastical Algorithms.” SIAM Journal on Computing. SIAM, 2019. https://doi.org/10.1137/16m109332x. ieee: D. Achlioptas, F. Iliopoulos, and V. Kolmogorov, “A local lemma for focused stochastical algorithms,” SIAM Journal on Computing, vol. 48, no. 5. SIAM, pp. 1583–1602, 2019. ista: Achlioptas D, Iliopoulos F, Kolmogorov V. 2019. A local lemma for focused stochastical algorithms. SIAM Journal on Computing. 48(5), 1583–1602. mla: Achlioptas, Dimitris, et al. “A Local Lemma for Focused Stochastical Algorithms.” SIAM Journal on Computing, vol. 48, no. 5, SIAM, 2019, pp. 1583–602, doi:10.1137/16m109332x. short: D. Achlioptas, F. Iliopoulos, V. Kolmogorov, SIAM Journal on Computing 48 (2019) 1583–1602. date_created: 2020-01-30T09:27:32Z date_published: 2019-10-31T00:00:00Z date_updated: 2023-09-06T15:25:29Z day: '31' department: - _id: VlKo doi: 10.1137/16m109332x ec_funded: 1 external_id: arxiv: - '1809.01537' isi: - '000493900200005' intvolume: ' 48' isi: 1 issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1809.01537 month: '10' oa: 1 oa_version: Preprint page: 1583-1602 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: SIAM Journal on Computing publication_identifier: eissn: - 1095-7111 issn: - 0097-5397 publication_status: published publisher: SIAM quality_controlled: '1' scopus_import: '1' status: public title: A local lemma for focused stochastical algorithms type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 48 year: '2019' ... --- _id: '7468' abstract: - lang: eng text: We present a new proximal bundle method for Maximum-A-Posteriori (MAP) inference in structured energy minimization problems. The method optimizes a Lagrangean relaxation of the original energy minimization problem using a multi plane block-coordinate Frank-Wolfe method that takes advantage of the specific structure of the Lagrangean decomposition. We show empirically that our method outperforms state-of-the-art Lagrangean decomposition based algorithms on some challenging Markov Random Field, multi-label discrete tomography and graph matching problems. article_number: 11138-11147 article_processing_charge: No author: - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Swoboda P, Kolmogorov V. Map inference via block-coordinate Frank-Wolfe algorithm. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol 2019-June. IEEE; 2019. doi:10.1109/CVPR.2019.01140' apa: 'Swoboda, P., & Kolmogorov, V. (2019). Map inference via block-coordinate Frank-Wolfe algorithm. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 2019–June). Long Beach, CA, United States: IEEE. https://doi.org/10.1109/CVPR.2019.01140' chicago: Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate Frank-Wolfe Algorithm.” In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2019–June. IEEE, 2019. https://doi.org/10.1109/CVPR.2019.01140. ieee: P. Swoboda and V. Kolmogorov, “Map inference via block-coordinate Frank-Wolfe algorithm,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Beach, CA, United States, 2019, vol. 2019–June. ista: 'Swoboda P, Kolmogorov V. 2019. Map inference via block-coordinate Frank-Wolfe algorithm. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition vol. 2019–June, 11138–11147.' mla: Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate Frank-Wolfe Algorithm.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2019–June, 11138–11147, IEEE, 2019, doi:10.1109/CVPR.2019.01140. short: P. Swoboda, V. Kolmogorov, in:, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, 2019. conference: end_date: 2019-06-20 location: Long Beach, CA, United States name: 'CVPR: Conference on Computer Vision and Pattern Recognition' start_date: 2019-06-15 date_created: 2020-02-09T23:00:52Z date_published: 2019-06-01T00:00:00Z date_updated: 2023-09-07T14:54:24Z day: '01' department: - _id: VlKo doi: 10.1109/CVPR.2019.01140 ec_funded: 1 external_id: arxiv: - '1806.05049' isi: - '000542649304076' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1806.05049 month: '06' oa: 1 oa_version: Preprint project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition publication_identifier: isbn: - '9781728132938' issn: - '10636919' publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Map inference via block-coordinate Frank-Wolfe algorithm type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2019-June year: '2019' ... --- _id: '7639' abstract: - lang: eng text: Deep neural networks (DNNs) have become increasingly important due to their excellent empirical performance on a wide range of problems. However, regularization is generally achieved by indirect means, largely due to the complex set of functions defined by a network and the difficulty in measuring function complexity. There exists no method in the literature for additive regularization based on a norm of the function, as is classically considered in statistical learning theory. In this work, we study the tractability of function norms for deep neural networks with ReLU activations. We provide, to the best of our knowledge, the first proof in the literature of the NP-hardness of computing function norms of DNNs of 3 or more layers. We also highlight a fundamental difference between shallow and deep networks. In the light on these results, we propose a new regularization strategy based on approximate function norms, and show its efficiency on a segmentation task with a DNN. article_number: 748-752 article_processing_charge: No author: - first_name: Amal full_name: Rannen-Triki, Amal last_name: Rannen-Triki - first_name: Maxim full_name: Berman, Maxim last_name: Berman - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Matthew B. full_name: Blaschko, Matthew B. last_name: Blaschko citation: ama: 'Rannen-Triki A, Berman M, Kolmogorov V, Blaschko MB. Function norms for neural networks. In: Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE; 2019. doi:10.1109/ICCVW.2019.00097' apa: 'Rannen-Triki, A., Berman, M., Kolmogorov, V., & Blaschko, M. B. (2019). Function norms for neural networks. In Proceedings of the 2019 International Conference on Computer Vision Workshop. Seoul, South Korea: IEEE. https://doi.org/10.1109/ICCVW.2019.00097' chicago: Rannen-Triki, Amal, Maxim Berman, Vladimir Kolmogorov, and Matthew B. Blaschko. “Function Norms for Neural Networks.” In Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE, 2019. https://doi.org/10.1109/ICCVW.2019.00097. ieee: A. Rannen-Triki, M. Berman, V. Kolmogorov, and M. B. Blaschko, “Function norms for neural networks,” in Proceedings of the 2019 International Conference on Computer Vision Workshop, Seoul, South Korea, 2019. ista: 'Rannen-Triki A, Berman M, Kolmogorov V, Blaschko MB. 2019. Function norms for neural networks. Proceedings of the 2019 International Conference on Computer Vision Workshop. ICCVW: International Conference on Computer Vision Workshop, 748–752.' mla: Rannen-Triki, Amal, et al. “Function Norms for Neural Networks.” Proceedings of the 2019 International Conference on Computer Vision Workshop, 748–752, IEEE, 2019, doi:10.1109/ICCVW.2019.00097. short: A. Rannen-Triki, M. Berman, V. Kolmogorov, M.B. Blaschko, in:, Proceedings of the 2019 International Conference on Computer Vision Workshop, IEEE, 2019. conference: end_date: 2019-10-28 location: Seoul, South Korea name: 'ICCVW: International Conference on Computer Vision Workshop' start_date: 2019-10-27 date_created: 2020-04-05T22:00:50Z date_published: 2019-10-01T00:00:00Z date_updated: 2023-09-08T11:19:12Z day: '01' department: - _id: VlKo doi: 10.1109/ICCVW.2019.00097 external_id: isi: - '000554591600090' isi: 1 language: - iso: eng month: '10' oa_version: None publication: Proceedings of the 2019 International Conference on Computer Vision Workshop publication_identifier: isbn: - '9781728150239' publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Function norms for neural networks type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2019' ... --- _id: '703' abstract: - lang: eng text: We consider the NP-hard problem of MAP-inference for undirected discrete graphical models. We propose a polynomial time and practically efficient algorithm for finding a part of its optimal solution. Specifically, our algorithm marks some labels of the considered graphical model either as (i) optimal, meaning that they belong to all optimal solutions of the inference problem; (ii) non-optimal if they provably do not belong to any solution. With access to an exact solver of a linear programming relaxation to the MAP-inference problem, our algorithm marks the maximal possible (in a specified sense) number of labels. We also present a version of the algorithm, which has access to a suboptimal dual solver only and still can ensure the (non-)optimality for the marked labels, although the overall number of the marked labels may decrease. We propose an efficient implementation, which runs in time comparable to a single run of a suboptimal dual solver. Our method is well-scalable and shows state-of-the-art results on computational benchmarks from machine learning and computer vision. author: - first_name: Alexander full_name: Shekhovtsov, Alexander last_name: Shekhovtsov - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Bogdan full_name: Savchynskyy, Bogdan last_name: Savchynskyy citation: ama: Shekhovtsov A, Swoboda P, Savchynskyy B. Maximum persistency via iterative relaxed inference with graphical models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018;40(7):1668-1682. doi:10.1109/TPAMI.2017.2730884 apa: Shekhovtsov, A., Swoboda, P., & Savchynskyy, B. (2018). Maximum persistency via iterative relaxed inference with graphical models. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2017.2730884 chicago: Shekhovtsov, Alexander, Paul Swoboda, and Bogdan Savchynskyy. “Maximum Persistency via Iterative Relaxed Inference with Graphical Models.” IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2018. https://doi.org/10.1109/TPAMI.2017.2730884. ieee: A. Shekhovtsov, P. Swoboda, and B. Savchynskyy, “Maximum persistency via iterative relaxed inference with graphical models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 7. IEEE, pp. 1668–1682, 2018. ista: Shekhovtsov A, Swoboda P, Savchynskyy B. 2018. Maximum persistency via iterative relaxed inference with graphical models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(7), 1668–1682. mla: Shekhovtsov, Alexander, et al. “Maximum Persistency via Iterative Relaxed Inference with Graphical Models.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 7, IEEE, 2018, pp. 1668–82, doi:10.1109/TPAMI.2017.2730884. short: A. Shekhovtsov, P. Swoboda, B. Savchynskyy, IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (2018) 1668–1682. date_created: 2018-12-11T11:48:01Z date_published: 2018-07-01T00:00:00Z date_updated: 2021-01-12T08:11:32Z day: '01' department: - _id: VlKo doi: 10.1109/TPAMI.2017.2730884 external_id: arxiv: - '1508.07902' intvolume: ' 40' issue: '7' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1508.07902 month: '07' oa: 1 oa_version: Preprint page: 1668-1682 publication: IEEE Transactions on Pattern Analysis and Machine Intelligence publication_identifier: issn: - '01628828' publication_status: published publisher: IEEE publist_id: '6992' quality_controlled: '1' scopus_import: 1 status: public title: Maximum persistency via iterative relaxed inference with graphical models type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 40 year: '2018' ... --- _id: '10864' abstract: - lang: eng text: We prove that every congruence distributive variety has directed Jónsson terms, and every congruence modular variety has directed Gumm terms. The directed terms we construct witness every case of absorption witnessed by the original Jónsson or Gumm terms. This result is equivalent to a pair of claims about absorption for admissible preorders in congruence distributive and congruence modular varieties, respectively. For finite algebras, these absorption theorems have already seen significant applications, but until now, it was not clear if the theorems hold for general algebras as well. Our method also yields a novel proof of a result by P. Lipparini about the existence of a chain of terms (which we call Pixley terms) in varieties that are at the same time congruence distributive and k-permutable for some k. acknowledgement: The second author was supported by National Science Center grant DEC-2011-/01/B/ST6/01006. article_processing_charge: No author: - first_name: Alexandr full_name: Kazda, Alexandr id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87 last_name: Kazda - first_name: Marcin full_name: Kozik, Marcin last_name: Kozik - first_name: Ralph full_name: McKenzie, Ralph last_name: McKenzie - first_name: Matthew full_name: Moore, Matthew last_name: Moore citation: ama: 'Kazda A, Kozik M, McKenzie R, Moore M. Absorption and directed Jónsson terms. In: Czelakowski J, ed. Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science. Vol 16. OCTR. Cham: Springer Nature; 2018:203-220. doi:10.1007/978-3-319-74772-9_7' apa: 'Kazda, A., Kozik, M., McKenzie, R., & Moore, M. (2018). Absorption and directed Jónsson terms. In J. Czelakowski (Ed.), Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science (Vol. 16, pp. 203–220). Cham: Springer Nature. https://doi.org/10.1007/978-3-319-74772-9_7' chicago: 'Kazda, Alexandr, Marcin Kozik, Ralph McKenzie, and Matthew Moore. “Absorption and Directed Jónsson Terms.” In Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science, edited by J Czelakowski, 16:203–20. OCTR. Cham: Springer Nature, 2018. https://doi.org/10.1007/978-3-319-74772-9_7.' ieee: 'A. Kazda, M. Kozik, R. McKenzie, and M. Moore, “Absorption and directed Jónsson terms,” in Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science, vol. 16, J. Czelakowski, Ed. Cham: Springer Nature, 2018, pp. 203–220.' ista: 'Kazda A, Kozik M, McKenzie R, Moore M. 2018.Absorption and directed Jónsson terms. In: Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science. vol. 16, 203–220.' mla: Kazda, Alexandr, et al. “Absorption and Directed Jónsson Terms.” Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science, edited by J Czelakowski, vol. 16, Springer Nature, 2018, pp. 203–20, doi:10.1007/978-3-319-74772-9_7. short: A. Kazda, M. Kozik, R. McKenzie, M. Moore, in:, J. Czelakowski (Ed.), Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science, Springer Nature, Cham, 2018, pp. 203–220. date_created: 2022-03-18T10:30:32Z date_published: 2018-03-21T00:00:00Z date_updated: 2023-09-05T15:37:18Z day: '21' department: - _id: VlKo doi: 10.1007/978-3-319-74772-9_7 editor: - first_name: J full_name: Czelakowski, J last_name: Czelakowski external_id: arxiv: - '1502.01072' intvolume: ' 16' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1502.01072 month: '03' oa: 1 oa_version: Preprint page: 203-220 place: Cham publication: Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science publication_identifier: eisbn: - '9783319747729' eissn: - 2211-2766 isbn: - '9783319747712' issn: - 2211-2758 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' series_title: OCTR status: public title: Absorption and directed Jónsson terms type: book_chapter user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 16 year: '2018' ... --- _id: '273' abstract: - lang: eng text: The accuracy of information retrieval systems is often measured using complex loss functions such as the average precision (AP) or the normalized discounted cumulative gain (NDCG). Given a set of positive and negative samples, the parameters of a retrieval system can be estimated by minimizing these loss functions. However, the non-differentiability and non-decomposability of these loss functions does not allow for simple gradient based optimization algorithms. This issue is generally circumvented by either optimizing a structured hinge-loss upper bound to the loss function or by using asymptotic methods like the direct-loss minimization framework. Yet, the high computational complexity of loss-augmented inference, which is necessary for both the frameworks, prohibits its use in large training data sets. To alleviate this deficiency, we present a novel quicksort flavored algorithm for a large class of non-decomposable loss functions. We provide a complete characterization of the loss functions that are amenable to our algorithm, and show that it includes both AP and NDCG based loss functions. Furthermore, we prove that no comparison based algorithm can improve upon the computational complexity of our approach asymptotically. We demonstrate the effectiveness of our approach in the context of optimizing the structured hinge loss upper bound of AP and NDCG loss for learning models for a variety of vision tasks. We show that our approach provides significantly better results than simpler decomposable loss functions, while requiring a comparable training time. article_processing_charge: No author: - first_name: Pritish full_name: Mohapatra, Pritish last_name: Mohapatra - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek - first_name: C V full_name: Jawahar, C V last_name: Jawahar - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: M Pawan full_name: Kumar, M Pawan last_name: Kumar citation: ama: 'Mohapatra P, Rolinek M, Jawahar CV, Kolmogorov V, Kumar MP. Efficient optimization for rank-based loss functions. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE; 2018:3693-3701. doi:10.1109/cvpr.2018.00389' apa: 'Mohapatra, P., Rolinek, M., Jawahar, C. V., Kolmogorov, V., & Kumar, M. P. (2018). Efficient optimization for rank-based loss functions. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3693–3701). Salt Lake City, UT, USA: IEEE. https://doi.org/10.1109/cvpr.2018.00389' chicago: Mohapatra, Pritish, Michal Rolinek, C V Jawahar, Vladimir Kolmogorov, and M Pawan Kumar. “Efficient Optimization for Rank-Based Loss Functions.” In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 3693–3701. IEEE, 2018. https://doi.org/10.1109/cvpr.2018.00389. ieee: P. Mohapatra, M. Rolinek, C. V. Jawahar, V. Kolmogorov, and M. P. Kumar, “Efficient optimization for rank-based loss functions,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 2018, pp. 3693–3701. ista: 'Mohapatra P, Rolinek M, Jawahar CV, Kolmogorov V, Kumar MP. 2018. Efficient optimization for rank-based loss functions. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition, 3693–3701.' mla: Mohapatra, Pritish, et al. “Efficient Optimization for Rank-Based Loss Functions.” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018, pp. 3693–701, doi:10.1109/cvpr.2018.00389. short: P. Mohapatra, M. Rolinek, C.V. Jawahar, V. Kolmogorov, M.P. Kumar, in:, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018, pp. 3693–3701. conference: end_date: 2018-06-22 location: Salt Lake City, UT, USA name: 'CVPR: Conference on Computer Vision and Pattern Recognition' start_date: 2018-06-18 date_created: 2018-12-11T11:45:33Z date_published: 2018-06-28T00:00:00Z date_updated: 2023-09-11T13:24:43Z day: '28' department: - _id: VlKo doi: 10.1109/cvpr.2018.00389 ec_funded: 1 external_id: arxiv: - '1604.08269' isi: - '000457843603087' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1604.08269 month: '06' oa: 1 oa_version: Preprint page: 3693-3701 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition publication_identifier: isbn: - '9781538664209' publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Efficient optimization for rank-based loss functions type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2018' ... --- _id: '193' abstract: - lang: eng text: 'We show attacks on five data-independent memory-hard functions (iMHF) that were submitted to the password hashing competition (PHC). Informally, an MHF is a function which cannot be evaluated on dedicated hardware, like ASICs, at significantly lower hardware and/or energy cost than evaluating a single instance on a standard single-core architecture. Data-independent means the memory access pattern of the function is independent of the input; this makes iMHFs harder to construct than data-dependent ones, but the latter can be attacked by various side-channel attacks. Following [Alwen-Blocki''16], we capture the evaluation of an iMHF as a directed acyclic graph (DAG). The cumulative parallel pebbling complexity of this DAG is a measure for the hardware cost of evaluating the iMHF on an ASIC. Ideally, one would like the complexity of a DAG underlying an iMHF to be as close to quadratic in the number of nodes of the graph as possible. Instead, we show that (the DAGs underlying) the following iMHFs are far from this bound: Rig.v2, TwoCats and Gambit each having an exponent no more than 1.75. Moreover, we show that the complexity of the iMHF modes of the PHC finalists Pomelo and Lyra2 have exponents at most 1.83 and 1.67 respectively. To show this we investigate a combinatorial property of each underlying DAG (called its depth-robustness. By establishing upper bounds on this property we are then able to apply the general technique of [Alwen-Block''16] for analyzing the hardware costs of an iMHF.' acknowledgement: Leonid Reyzin was supported in part by IST Austria and by US NSF grants 1012910, 1012798, and 1422965; this research was performed while he was visiting IST Austria. article_processing_charge: No author: - first_name: Joel F full_name: Alwen, Joel F id: 2A8DFA8C-F248-11E8-B48F-1D18A9856A87 last_name: Alwen - first_name: Peter full_name: Gazi, Peter last_name: Gazi - first_name: Chethan full_name: Kamath Hosdurg, Chethan id: 4BD3F30E-F248-11E8-B48F-1D18A9856A87 last_name: Kamath Hosdurg - first_name: Karen full_name: Klein, Karen id: 3E83A2F8-F248-11E8-B48F-1D18A9856A87 last_name: Klein - first_name: Georg F full_name: Osang, Georg F id: 464B40D6-F248-11E8-B48F-1D18A9856A87 last_name: Osang orcid: 0000-0002-8882-5116 - first_name: Krzysztof Z full_name: Pietrzak, Krzysztof Z id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87 last_name: Pietrzak orcid: 0000-0002-9139-1654 - first_name: Lenoid full_name: Reyzin, Lenoid last_name: Reyzin - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek - first_name: Michal full_name: Rybar, Michal id: 2B3E3DE8-F248-11E8-B48F-1D18A9856A87 last_name: Rybar citation: ama: 'Alwen JF, Gazi P, Kamath Hosdurg C, et al. On the memory hardness of data independent password hashing functions. In: Proceedings of the 2018 on Asia Conference on Computer and Communication Security. ACM; 2018:51-65. doi:10.1145/3196494.3196534' apa: 'Alwen, J. F., Gazi, P., Kamath Hosdurg, C., Klein, K., Osang, G. F., Pietrzak, K. Z., … Rybar, M. (2018). On the memory hardness of data independent password hashing functions. In Proceedings of the 2018 on Asia Conference on Computer and Communication Security (pp. 51–65). Incheon, Republic of Korea: ACM. https://doi.org/10.1145/3196494.3196534' chicago: Alwen, Joel F, Peter Gazi, Chethan Kamath Hosdurg, Karen Klein, Georg F Osang, Krzysztof Z Pietrzak, Lenoid Reyzin, Michal Rolinek, and Michal Rybar. “On the Memory Hardness of Data Independent Password Hashing Functions.” In Proceedings of the 2018 on Asia Conference on Computer and Communication Security, 51–65. ACM, 2018. https://doi.org/10.1145/3196494.3196534. ieee: J. F. Alwen et al., “On the memory hardness of data independent password hashing functions,” in Proceedings of the 2018 on Asia Conference on Computer and Communication Security, Incheon, Republic of Korea, 2018, pp. 51–65. ista: 'Alwen JF, Gazi P, Kamath Hosdurg C, Klein K, Osang GF, Pietrzak KZ, Reyzin L, Rolinek M, Rybar M. 2018. On the memory hardness of data independent password hashing functions. Proceedings of the 2018 on Asia Conference on Computer and Communication Security. ASIACCS: Asia Conference on Computer and Communications Security , 51–65.' mla: Alwen, Joel F., et al. “On the Memory Hardness of Data Independent Password Hashing Functions.” Proceedings of the 2018 on Asia Conference on Computer and Communication Security, ACM, 2018, pp. 51–65, doi:10.1145/3196494.3196534. short: J.F. Alwen, P. Gazi, C. Kamath Hosdurg, K. Klein, G.F. Osang, K.Z. Pietrzak, L. Reyzin, M. Rolinek, M. Rybar, in:, Proceedings of the 2018 on Asia Conference on Computer and Communication Security, ACM, 2018, pp. 51–65. conference: end_date: 2018-06-08 location: Incheon, Republic of Korea name: 'ASIACCS: Asia Conference on Computer and Communications Security ' start_date: 2018-06-04 date_created: 2018-12-11T11:45:07Z date_published: 2018-06-01T00:00:00Z date_updated: 2023-09-13T09:13:12Z day: '01' department: - _id: KrPi - _id: HeEd - _id: VlKo doi: 10.1145/3196494.3196534 ec_funded: 1 external_id: isi: - '000516620100005' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://eprint.iacr.org/2016/783 month: '06' oa: 1 oa_version: Submitted Version page: 51 - 65 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' - _id: 258AA5B2-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '682815' name: Teaching Old Crypto New Tricks publication: Proceedings of the 2018 on Asia Conference on Computer and Communication Security publication_status: published publisher: ACM publist_id: '7723' quality_controlled: '1' scopus_import: '1' status: public title: On the memory hardness of data independent password hashing functions type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2018' ... --- _id: '5975' abstract: - lang: eng text: We consider the recent formulation of the algorithmic Lov ́asz Local Lemma [N. Har-vey and J. Vondr ́ak, inProceedings of FOCS, 2015, pp. 1327–1345; D. Achlioptas and F. Iliopoulos,inProceedings of SODA, 2016, pp. 2024–2038; D. Achlioptas, F. Iliopoulos, and V. Kolmogorov,ALocal Lemma for Focused Stochastic Algorithms, arXiv preprint, 2018] for finding objects that avoid“bad features,” or “flaws.” It extends the Moser–Tardos resampling algorithm [R. A. Moser andG. Tardos,J. ACM, 57 (2010), 11] to more general discrete spaces. At each step the method picks aflaw present in the current state and goes to a new state according to some prespecified probabilitydistribution (which depends on the current state and the selected flaw). However, the recent formu-lation is less flexible than the Moser–Tardos method since it requires a specific flaw selection rule,whereas the algorithm of Moser and Tardos allows an arbitrary rule (and thus can potentially beimplemented more efficiently). We formulate a new “commutativity” condition and prove that it issufficient for an arbitrary rule to work. It also enables an efficient parallelization under an additionalassumption. We then show that existing resampling oracles for perfect matchings and permutationsdo satisfy this condition. article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Kolmogorov V. Commutativity in the algorithmic Lovász local lemma. SIAM Journal on Computing. 2018;47(6):2029-2056. doi:10.1137/16m1093306 apa: Kolmogorov, V. (2018). Commutativity in the algorithmic Lovász local lemma. SIAM Journal on Computing. Society for Industrial & Applied Mathematics (SIAM). https://doi.org/10.1137/16m1093306 chicago: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovász Local Lemma.” SIAM Journal on Computing. Society for Industrial & Applied Mathematics (SIAM), 2018. https://doi.org/10.1137/16m1093306. ieee: V. Kolmogorov, “Commutativity in the algorithmic Lovász local lemma,” SIAM Journal on Computing, vol. 47, no. 6. Society for Industrial & Applied Mathematics (SIAM), pp. 2029–2056, 2018. ista: Kolmogorov V. 2018. Commutativity in the algorithmic Lovász local lemma. SIAM Journal on Computing. 47(6), 2029–2056. mla: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovász Local Lemma.” SIAM Journal on Computing, vol. 47, no. 6, Society for Industrial & Applied Mathematics (SIAM), 2018, pp. 2029–56, doi:10.1137/16m1093306. short: V. Kolmogorov, SIAM Journal on Computing 47 (2018) 2029–2056. date_created: 2019-02-13T12:59:33Z date_published: 2018-11-08T00:00:00Z date_updated: 2023-09-19T14:24:58Z day: '08' department: - _id: VlKo doi: 10.1137/16m1093306 ec_funded: 1 external_id: arxiv: - '1506.08547' isi: - '000453785100001' intvolume: ' 47' isi: 1 issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1506.08547 month: '11' oa: 1 oa_version: Preprint page: 2029-2056 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: SIAM Journal on Computing publication_identifier: eissn: - 1095-7111 issn: - 0097-5397 publication_status: published publisher: Society for Industrial & Applied Mathematics (SIAM) quality_controlled: '1' related_material: record: - id: '1193' relation: earlier_version status: public scopus_import: '1' status: public title: Commutativity in the algorithmic Lovász local lemma type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 47 year: '2018' ... --- _id: '5978' abstract: - lang: eng text: 'We consider the MAP-inference problem for graphical models,which is a valued constraint satisfaction problem defined onreal numbers with a natural summation operation. We proposea family of relaxations (different from the famous Sherali-Adams hierarchy), which naturally define lower bounds for itsoptimum. This family always contains a tight relaxation andwe give an algorithm able to find it and therefore, solve theinitial non-relaxed NP-hard problem.The relaxations we consider decompose the original probleminto two non-overlapping parts: an easy LP-tight part and adifficult one. For the latter part a combinatorial solver must beused. As we show in our experiments, in a number of applica-tions the second, difficult part constitutes only a small fractionof the whole problem. This property allows to significantlyreduce the computational time of the combinatorial solver andtherefore solve problems which were out of reach before.' article_processing_charge: No author: - first_name: Stefan full_name: Haller, Stefan last_name: Haller - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Bogdan full_name: Savchynskyy, Bogdan last_name: Savchynskyy citation: ama: 'Haller S, Swoboda P, Savchynskyy B. Exact MAP-inference by confining combinatorial search with LP relaxation. In: Proceedings of the 32st AAAI Conference on Artificial Intelligence. AAAI Press; 2018:6581-6588.' apa: 'Haller, S., Swoboda, P., & Savchynskyy, B. (2018). Exact MAP-inference by confining combinatorial search with LP relaxation. In Proceedings of the 32st AAAI Conference on Artificial Intelligence (pp. 6581–6588). New Orleans, LU, United States: AAAI Press.' chicago: Haller, Stefan, Paul Swoboda, and Bogdan Savchynskyy. “Exact MAP-Inference by Confining Combinatorial Search with LP Relaxation.” In Proceedings of the 32st AAAI Conference on Artificial Intelligence, 6581–88. AAAI Press, 2018. ieee: S. Haller, P. Swoboda, and B. Savchynskyy, “Exact MAP-inference by confining combinatorial search with LP relaxation,” in Proceedings of the 32st AAAI Conference on Artificial Intelligence, New Orleans, LU, United States, 2018, pp. 6581–6588. ista: 'Haller S, Swoboda P, Savchynskyy B. 2018. Exact MAP-inference by confining combinatorial search with LP relaxation. Proceedings of the 32st AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence, 6581–6588.' mla: Haller, Stefan, et al. “Exact MAP-Inference by Confining Combinatorial Search with LP Relaxation.” Proceedings of the 32st AAAI Conference on Artificial Intelligence, AAAI Press, 2018, pp. 6581–88. short: S. Haller, P. Swoboda, B. Savchynskyy, in:, Proceedings of the 32st AAAI Conference on Artificial Intelligence, AAAI Press, 2018, pp. 6581–6588. conference: end_date: 2018-02-07 location: New Orleans, LU, United States name: 'AAAI: Conference on Artificial Intelligence' start_date: 2018-02-02 date_created: 2019-02-13T13:32:48Z date_published: 2018-02-01T00:00:00Z date_updated: 2023-09-19T14:26:52Z day: '01' department: - _id: VlKo external_id: arxiv: - '2004.06370' isi: - '000485488906082' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2004.06370 month: '02' oa: 1 oa_version: Preprint page: 6581-6588 publication: Proceedings of the 32st AAAI Conference on Artificial Intelligence publication_status: published publisher: AAAI Press quality_controlled: '1' scopus_import: '1' status: public title: Exact MAP-inference by confining combinatorial search with LP relaxation type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2018' ... --- _id: '18' abstract: - lang: eng text: An N-superconcentrator is a directed, acyclic graph with N input nodes and N output nodes such that every subset of the inputs and every subset of the outputs of same cardinality can be connected by node-disjoint paths. It is known that linear-size and bounded-degree superconcentrators exist. We prove the existence of such superconcentrators with asymptotic density 25.3 (where the density is the number of edges divided by N). The previously best known densities were 28 [12] and 27.4136 [17]. article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: Kolmogorov V, Rolinek M. Superconcentrators of density 25.3. Ars Combinatoria. 2018;141(10):269-304. apa: Kolmogorov, V., & Rolinek, M. (2018). Superconcentrators of density 25.3. Ars Combinatoria. Charles Babbage Research Centre. chicago: Kolmogorov, Vladimir, and Michal Rolinek. “Superconcentrators of Density 25.3.” Ars Combinatoria. Charles Babbage Research Centre, 2018. ieee: V. Kolmogorov and M. Rolinek, “Superconcentrators of density 25.3,” Ars Combinatoria, vol. 141, no. 10. Charles Babbage Research Centre, pp. 269–304, 2018. ista: Kolmogorov V, Rolinek M. 2018. Superconcentrators of density 25.3. Ars Combinatoria. 141(10), 269–304. mla: Kolmogorov, Vladimir, and Michal Rolinek. “Superconcentrators of Density 25.3.” Ars Combinatoria, vol. 141, no. 10, Charles Babbage Research Centre, 2018, pp. 269–304. short: V. Kolmogorov, M. Rolinek, Ars Combinatoria 141 (2018) 269–304. date_created: 2018-12-11T11:44:11Z date_published: 2018-10-01T00:00:00Z date_updated: 2023-09-19T14:46:18Z day: '01' department: - _id: VlKo external_id: arxiv: - '1405.7828' isi: - '000446809500022' intvolume: ' 141' isi: 1 issue: '10' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1405.7828 month: '10' oa: 1 oa_version: Preprint page: 269 - 304 publication: Ars Combinatoria publication_identifier: issn: - 0381-7032 publication_status: published publisher: Charles Babbage Research Centre publist_id: '8037' quality_controlled: '1' scopus_import: '1' status: public title: Superconcentrators of density 25.3 type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 141 year: '2018' ... --- _id: '6032' abstract: - lang: eng text: The main result of this article is a generalization of the classical blossom algorithm for finding perfect matchings. Our algorithm can efficiently solve Boolean CSPs where each variable appears in exactly two constraints (we call it edge CSP) and all constraints are even Δ-matroid relations (represented by lists of tuples). As a consequence of this, we settle the complexity classification of planar Boolean CSPs started by Dvorak and Kupec. Using a reduction to even Δ-matroids, we then extend the tractability result to larger classes of Δ-matroids that we call efficiently coverable. It properly includes classes that were known to be tractable before, namely, co-independent, compact, local, linear, and binary, with the following caveat:We represent Δ-matroids by lists of tuples, while the last two use a representation by matrices. Since an n ×n matrix can represent exponentially many tuples, our tractability result is not strictly stronger than the known algorithm for linear and binary Δ-matroids. article_number: '22' article_processing_charge: No article_type: original author: - first_name: Alexandr full_name: Kazda, Alexandr id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87 last_name: Kazda - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: Kazda A, Kolmogorov V, Rolinek M. Even delta-matroids and the complexity of planar boolean CSPs. ACM Transactions on Algorithms. 2018;15(2). doi:10.1145/3230649 apa: Kazda, A., Kolmogorov, V., & Rolinek, M. (2018). Even delta-matroids and the complexity of planar boolean CSPs. ACM Transactions on Algorithms. ACM. https://doi.org/10.1145/3230649 chicago: Kazda, Alexandr, Vladimir Kolmogorov, and Michal Rolinek. “Even Delta-Matroids and the Complexity of Planar Boolean CSPs.” ACM Transactions on Algorithms. ACM, 2018. https://doi.org/10.1145/3230649. ieee: A. Kazda, V. Kolmogorov, and M. Rolinek, “Even delta-matroids and the complexity of planar boolean CSPs,” ACM Transactions on Algorithms, vol. 15, no. 2. ACM, 2018. ista: Kazda A, Kolmogorov V, Rolinek M. 2018. Even delta-matroids and the complexity of planar boolean CSPs. ACM Transactions on Algorithms. 15(2), 22. mla: Kazda, Alexandr, et al. “Even Delta-Matroids and the Complexity of Planar Boolean CSPs.” ACM Transactions on Algorithms, vol. 15, no. 2, 22, ACM, 2018, doi:10.1145/3230649. short: A. Kazda, V. Kolmogorov, M. Rolinek, ACM Transactions on Algorithms 15 (2018). date_created: 2019-02-17T22:59:25Z date_published: 2018-12-01T00:00:00Z date_updated: 2023-09-20T11:20:26Z day: '01' department: - _id: VlKo doi: 10.1145/3230649 ec_funded: 1 external_id: arxiv: - '1602.03124' isi: - '000468036500007' intvolume: ' 15' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1602.03124 month: '12' oa: 1 oa_version: Preprint project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: ACM Transactions on Algorithms publication_status: published publisher: ACM quality_controlled: '1' related_material: record: - id: '1192' relation: earlier_version status: public scopus_import: '1' status: public title: Even delta-matroids and the complexity of planar boolean CSPs type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 15 year: '2018' ... --- _id: '5573' abstract: - lang: eng text: Graph matching problems for large displacement optical flow of RGB-D images. article_processing_charge: No author: - first_name: Hassan full_name: Alhaija, Hassan last_name: Alhaija - first_name: Anita full_name: Sellent, Anita last_name: Sellent - first_name: Daniel full_name: Kondermann, Daniel last_name: Kondermann - first_name: Carsten full_name: Rother, Carsten last_name: Rother citation: ama: Alhaija H, Sellent A, Kondermann D, Rother C. Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow. 2018. doi:10.15479/AT:ISTA:82 apa: Alhaija, H., Sellent, A., Kondermann, D., & Rother, C. (2018). Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:82 chicago: Alhaija, Hassan, Anita Sellent, Daniel Kondermann, and Carsten Rother. “Graph Matching Problems for GraphFlow – 6D Large Displacement Scene Flow.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:82. ieee: H. Alhaija, A. Sellent, D. Kondermann, and C. Rother, “Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow.” Institute of Science and Technology Austria, 2018. ista: Alhaija H, Sellent A, Kondermann D, Rother C. 2018. Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow, Institute of Science and Technology Austria, 10.15479/AT:ISTA:82. mla: Alhaija, Hassan, et al. Graph Matching Problems for GraphFlow – 6D Large Displacement Scene Flow. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:82. short: H. Alhaija, A. Sellent, D. Kondermann, C. Rother, (2018). contributor: - contributor_type: researcher first_name: Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda datarep_id: '82' date_created: 2018-12-12T12:31:36Z date_published: 2018-01-04T00:00:00Z date_updated: 2024-02-21T13:41:17Z day: '04' ddc: - '001' department: - _id: VlKo doi: 10.15479/AT:ISTA:82 file: - access_level: open_access checksum: 53c17082848e12f3c2e1b4185b578208 content_type: application/zip creator: system date_created: 2018-12-12T13:02:34Z date_updated: 2020-07-14T12:47:05Z file_id: '5600' file_name: IST-2018-82-v1+1_GraphFlowMatchingProblems.zip file_size: 1737958 relation: main_file file_date_updated: 2020-07-14T12:47:05Z has_accepted_license: '1' keyword: - graph matching - quadratic assignment problem< license: https://creativecommons.org/publicdomain/zero/1.0/ month: '01' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria related_material: link: - relation: research_paper url: https://doi.org/10.1007/978-3-319-24947-6_23 status: public title: Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '641' abstract: - lang: eng text: 'We introduce two novel methods for learning parameters of graphical models for image labelling. The following two tasks underline both methods: (i) perturb model parameters based on given features and ground truth labelings, so as to exactly reproduce these labelings as optima of the local polytope relaxation of the labelling problem; (ii) train a predictor for the perturbed model parameters so that improved model parameters can be applied to the labelling of novel data. Our first method implements task (i) by inverse linear programming and task (ii) using a regressor e.g. a Gaussian process. Our second approach simultaneously solves tasks (i) and (ii) in a joint manner, while being restricted to linearly parameterised predictors. Experiments demonstrate the merits of both approaches.' alternative_title: - LNCS author: - first_name: Vera full_name: Trajkovska, Vera last_name: Trajkovska - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Freddie full_name: Åström, Freddie last_name: Åström - first_name: Stefanie full_name: Petra, Stefanie last_name: Petra citation: ama: 'Trajkovska V, Swoboda P, Åström F, Petra S. Graphical model parameter learning by inverse linear programming. In: Lauze F, Dong Y, Bjorholm Dahl A, eds. Vol 10302. Springer; 2017:323-334. doi:10.1007/978-3-319-58771-4_26' apa: 'Trajkovska, V., Swoboda, P., Åström, F., & Petra, S. (2017). Graphical model parameter learning by inverse linear programming. In F. Lauze, Y. Dong, & A. Bjorholm Dahl (Eds.) (Vol. 10302, pp. 323–334). Presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark: Springer. https://doi.org/10.1007/978-3-319-58771-4_26' chicago: Trajkovska, Vera, Paul Swoboda, Freddie Åström, and Stefanie Petra. “Graphical Model Parameter Learning by Inverse Linear Programming.” edited by François Lauze, Yiqiu Dong, and Anders Bjorholm Dahl, 10302:323–34. Springer, 2017. https://doi.org/10.1007/978-3-319-58771-4_26. ieee: 'V. Trajkovska, P. Swoboda, F. Åström, and S. Petra, “Graphical model parameter learning by inverse linear programming,” presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark, 2017, vol. 10302, pp. 323–334.' ista: 'Trajkovska V, Swoboda P, Åström F, Petra S. 2017. Graphical model parameter learning by inverse linear programming. SSVM: Scale Space and Variational Methods in Computer Vision, LNCS, vol. 10302, 323–334.' mla: Trajkovska, Vera, et al. Graphical Model Parameter Learning by Inverse Linear Programming. Edited by François Lauze et al., vol. 10302, Springer, 2017, pp. 323–34, doi:10.1007/978-3-319-58771-4_26. short: V. Trajkovska, P. Swoboda, F. Åström, S. Petra, in:, F. Lauze, Y. Dong, A. Bjorholm Dahl (Eds.), Springer, 2017, pp. 323–334. conference: end_date: 2017-06-08 location: Kolding, Denmark name: 'SSVM: Scale Space and Variational Methods in Computer Vision' start_date: 2017-06-04 date_created: 2018-12-11T11:47:39Z date_published: 2017-01-01T00:00:00Z date_updated: 2021-01-12T08:07:23Z day: '01' department: - _id: VlKo doi: 10.1007/978-3-319-58771-4_26 editor: - first_name: François full_name: Lauze, François last_name: Lauze - first_name: Yiqiu full_name: Dong, Yiqiu last_name: Dong - first_name: Anders full_name: Bjorholm Dahl, Anders last_name: Bjorholm Dahl intvolume: ' 10302' language: - iso: eng month: '01' oa_version: None page: 323 - 334 publication_identifier: isbn: - 978-331958770-7 publication_status: published publisher: Springer publist_id: '7147' quality_controlled: '1' scopus_import: 1 status: public title: Graphical model parameter learning by inverse linear programming type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 10302 year: '2017' ... --- _id: '644' abstract: - lang: eng text: An instance of the valued constraint satisfaction problem (VCSP) is given by a finite set of variables, a finite domain of labels, and a sum of functions, each function depending on a subset of the variables. Each function can take finite values specifying costs of assignments of labels to its variables or the infinite value, which indicates an infeasible assignment. The goal is to find an assignment of labels to the variables that minimizes the sum. We study, assuming that P 6= NP, how the complexity of this very general problem depends on the set of functions allowed in the instances, the so-called constraint language. The case when all allowed functions take values in f0;1g corresponds to ordinary CSPs, where one deals only with the feasibility issue, and there is no optimization. This case is the subject of the algebraic CSP dichotomy conjecture predicting for which constraint languages CSPs are tractable (i.e., solvable in polynomial time) and for which they are NP-hard. The case when all allowed functions take only finite values corresponds to a finitevalued CSP, where the feasibility aspect is trivial and one deals only with the optimization issue. The complexity of finite-valued CSPs was fully classified by Thapper and Živný. An algebraic necessary condition for tractability of a general-valued CSP with a fixed constraint language was recently given by Kozik and Ochremiak. As our main result, we prove that if a constraint language satisfies this algebraic necessary condition, and the feasibility CSP (i.e., the problem of deciding whether a given instance has a feasible solution) corresponding to the VCSP with this language is tractable, then the VCSP is tractable. The algorithm is a simple combination of the assumed algorithm for the feasibility CSP and the standard LP relaxation. As a corollary, we obtain that a dichotomy for ordinary CSPs would imply a dichotomy for general-valued CSPs. author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Andrei full_name: Krokhin, Andrei last_name: Krokhin - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: Kolmogorov V, Krokhin A, Rolinek M. The complexity of general-valued CSPs. SIAM Journal on Computing. 2017;46(3):1087-1110. doi:10.1137/16M1091836 apa: Kolmogorov, V., Krokhin, A., & Rolinek, M. (2017). The complexity of general-valued CSPs. SIAM Journal on Computing. SIAM. https://doi.org/10.1137/16M1091836 chicago: Kolmogorov, Vladimir, Andrei Krokhin, and Michal Rolinek. “The Complexity of General-Valued CSPs.” SIAM Journal on Computing. SIAM, 2017. https://doi.org/10.1137/16M1091836. ieee: V. Kolmogorov, A. Krokhin, and M. Rolinek, “The complexity of general-valued CSPs,” SIAM Journal on Computing, vol. 46, no. 3. SIAM, pp. 1087–1110, 2017. ista: Kolmogorov V, Krokhin A, Rolinek M. 2017. The complexity of general-valued CSPs. SIAM Journal on Computing. 46(3), 1087–1110. mla: Kolmogorov, Vladimir, et al. “The Complexity of General-Valued CSPs.” SIAM Journal on Computing, vol. 46, no. 3, SIAM, 2017, pp. 1087–110, doi:10.1137/16M1091836. short: V. Kolmogorov, A. Krokhin, M. Rolinek, SIAM Journal on Computing 46 (2017) 1087–1110. date_created: 2018-12-11T11:47:40Z date_published: 2017-06-29T00:00:00Z date_updated: 2023-02-23T10:07:49Z day: '29' department: - _id: VlKo doi: 10.1137/16M1091836 ec_funded: 1 intvolume: ' 46' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1502.07327 month: '06' oa: 1 oa_version: Preprint page: 1087 - 1110 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: SIAM Journal on Computing publication_status: published publisher: SIAM publist_id: '7138' quality_controlled: '1' related_material: record: - id: '1637' relation: other status: public scopus_import: 1 status: public title: The complexity of general-valued CSPs type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 46 year: '2017' ... --- _id: '646' abstract: - lang: eng text: We present a novel convex relaxation and a corresponding inference algorithm for the non-binary discrete tomography problem, that is, reconstructing discrete-valued images from few linear measurements. In contrast to state of the art approaches that split the problem into a continuous reconstruction problem for the linear measurement constraints and a discrete labeling problem to enforce discrete-valued reconstructions, we propose a joint formulation that addresses both problems simultaneously, resulting in a tighter convex relaxation. For this purpose a constrained graphical model is set up and evaluated using a novel relaxation optimized by dual decomposition. We evaluate our approach experimentally and show superior solutions both mathematically (tighter relaxation) and experimentally in comparison to previously proposed relaxations. alternative_title: - LNCS author: - first_name: Jan full_name: Kuske, Jan last_name: Kuske - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Stefanie full_name: Petra, Stefanie last_name: Petra citation: ama: 'Kuske J, Swoboda P, Petra S. A novel convex relaxation for non binary discrete tomography. In: Lauze F, Dong Y, Bjorholm Dahl A, eds. Vol 10302. Springer; 2017:235-246. doi:10.1007/978-3-319-58771-4_19' apa: 'Kuske, J., Swoboda, P., & Petra, S. (2017). A novel convex relaxation for non binary discrete tomography. In F. Lauze, Y. Dong, & A. Bjorholm Dahl (Eds.) (Vol. 10302, pp. 235–246). Presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark: Springer. https://doi.org/10.1007/978-3-319-58771-4_19' chicago: Kuske, Jan, Paul Swoboda, and Stefanie Petra. “A Novel Convex Relaxation for Non Binary Discrete Tomography.” edited by François Lauze, Yiqiu Dong, and Anders Bjorholm Dahl, 10302:235–46. Springer, 2017. https://doi.org/10.1007/978-3-319-58771-4_19. ieee: 'J. Kuske, P. Swoboda, and S. Petra, “A novel convex relaxation for non binary discrete tomography,” presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark, 2017, vol. 10302, pp. 235–246.' ista: 'Kuske J, Swoboda P, Petra S. 2017. A novel convex relaxation for non binary discrete tomography. SSVM: Scale Space and Variational Methods in Computer Vision, LNCS, vol. 10302, 235–246.' mla: Kuske, Jan, et al. A Novel Convex Relaxation for Non Binary Discrete Tomography. Edited by François Lauze et al., vol. 10302, Springer, 2017, pp. 235–46, doi:10.1007/978-3-319-58771-4_19. short: J. Kuske, P. Swoboda, S. Petra, in:, F. Lauze, Y. Dong, A. Bjorholm Dahl (Eds.), Springer, 2017, pp. 235–246. conference: end_date: 2017-06-08 location: Kolding, Denmark name: 'SSVM: Scale Space and Variational Methods in Computer Vision' start_date: 2017-06-04 date_created: 2018-12-11T11:47:41Z date_published: 2017-06-01T00:00:00Z date_updated: 2021-01-12T08:07:34Z day: '01' department: - _id: VlKo doi: 10.1007/978-3-319-58771-4_19 ec_funded: 1 editor: - first_name: François full_name: Lauze, François last_name: Lauze - first_name: Yiqiu full_name: Dong, Yiqiu last_name: Dong - first_name: Anders full_name: Bjorholm Dahl, Anders last_name: Bjorholm Dahl intvolume: ' 10302' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1703.03769 month: '06' oa: 1 oa_version: Submitted Version page: 235 - 246 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_identifier: isbn: - 978-331958770-7 publication_status: published publisher: Springer publist_id: '7132' quality_controlled: '1' scopus_import: 1 status: public title: A novel convex relaxation for non binary discrete tomography type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 10302 year: '2017' ... --- _id: '992' abstract: - lang: eng text: "An instance of the Constraint Satisfaction Problem (CSP) is given by a finite set of\r\nvariables, a finite domain of labels, and a set of constraints, each constraint acting on\r\na subset of the variables. The goal is to find an assignment of labels to its variables\r\nthat satisfies all constraints (or decide whether one exists). If we allow more general\r\n“soft” constraints, which come with (possibly infinite) costs of particular assignments,\r\nwe obtain instances from a richer class called Valued Constraint Satisfaction Problem\r\n(VCSP). There the goal is to find an assignment with minimum total cost.\r\nIn this thesis, we focus (assuming that P\r\n6\r\n=\r\nNP) on classifying computational com-\r\nplexity of CSPs and VCSPs under certain restricting conditions. Two results are the core\r\ncontent of the work. In one of them, we consider VCSPs parametrized by a constraint\r\nlanguage, that is the set of “soft” constraints allowed to form the instances, and finish\r\nthe complexity classification modulo (missing pieces of) complexity classification for\r\nanalogously parametrized CSP. The other result is a generalization of Edmonds’ perfect\r\nmatching algorithm. This generalization contributes to complexity classfications in two\r\nways. First, it gives a new (largest known) polynomial-time solvable class of Boolean\r\nCSPs in which every variable may appear in at most two constraints and second, it\r\nsettles full classification of Boolean CSPs with planar drawing (again parametrized by a\r\nconstraint language)." acknowledgement: FP7/2007-2013/ERC grant agreement no 616160 alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: Rolinek M. Complexity of constraint satisfaction. 2017. doi:10.15479/AT:ISTA:th_815 apa: Rolinek, M. (2017). Complexity of constraint satisfaction. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_815 chicago: Rolinek, Michal. “Complexity of Constraint Satisfaction.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_815. ieee: M. Rolinek, “Complexity of constraint satisfaction,” Institute of Science and Technology Austria, 2017. ista: Rolinek M. 2017. Complexity of constraint satisfaction. Institute of Science and Technology Austria. mla: Rolinek, Michal. Complexity of Constraint Satisfaction. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_815. short: M. Rolinek, Complexity of Constraint Satisfaction, Institute of Science and Technology Austria, 2017. date_created: 2018-12-11T11:49:35Z date_published: 2017-05-01T00:00:00Z date_updated: 2023-09-07T12:05:41Z day: '01' ddc: - '004' degree_awarded: PhD department: - _id: VlKo doi: 10.15479/AT:ISTA:th_815 ec_funded: 1 file: - access_level: open_access checksum: 81761fb939acb7585c36629f765b4373 content_type: application/pdf creator: system date_created: 2018-12-12T10:07:55Z date_updated: 2020-07-14T12:48:18Z file_id: '4654' file_name: IST-2017-815-v1+3_final_blank_signature_maybe_pdfa.pdf file_size: 786145 relation: main_file - access_level: closed checksum: 2b2d7e1d6c1c79a9795a7aa0f860baf3 content_type: application/zip creator: dernst date_created: 2019-04-05T08:43:24Z date_updated: 2020-07-14T12:48:18Z file_id: '6208' file_name: 2017_Thesis_Rolinek_source.zip file_size: 5936337 relation: source_file file_date_updated: 2020-07-14T12:48:18Z has_accepted_license: '1' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '97' project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publist_id: '6407' pubrep_id: '815' status: public supervisor: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov title: Complexity of constraint satisfaction type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2017' ... --- _id: '1192' abstract: - lang: eng text: The main result of this paper is a generalization of the classical blossom algorithm for finding perfect matchings. Our algorithm can efficiently solve Boolean CSPs where each variable appears in exactly two constraints (we call it edge CSP) and all constraints are even Δ-matroid relations (represented by lists of tuples). As a consequence of this, we settle the complexity classification of planar Boolean CSPs started by Dvorak and Kupec. Knowing that edge CSP is tractable for even Δ-matroid constraints allows us to extend the tractability result to a larger class of Δ-matroids that includes many classes that were known to be tractable before, namely co-independent, compact, local and binary. article_processing_charge: No author: - first_name: Alexandr full_name: Kazda, Alexandr id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87 last_name: Kazda - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: 'Kazda A, Kolmogorov V, Rolinek M. Even delta-matroids and the complexity of planar Boolean CSPs. In: SIAM; 2017:307-326. doi:10.1137/1.9781611974782.20' apa: 'Kazda, A., Kolmogorov, V., & Rolinek, M. (2017). Even delta-matroids and the complexity of planar Boolean CSPs (pp. 307–326). Presented at the SODA: Symposium on Discrete Algorithms, Barcelona, Spain: SIAM. https://doi.org/10.1137/1.9781611974782.20' chicago: Kazda, Alexandr, Vladimir Kolmogorov, and Michal Rolinek. “Even Delta-Matroids and the Complexity of Planar Boolean CSPs,” 307–26. SIAM, 2017. https://doi.org/10.1137/1.9781611974782.20. ieee: 'A. Kazda, V. Kolmogorov, and M. Rolinek, “Even delta-matroids and the complexity of planar Boolean CSPs,” presented at the SODA: Symposium on Discrete Algorithms, Barcelona, Spain, 2017, pp. 307–326.' ista: 'Kazda A, Kolmogorov V, Rolinek M. 2017. Even delta-matroids and the complexity of planar Boolean CSPs. SODA: Symposium on Discrete Algorithms, 307–326.' mla: Kazda, Alexandr, et al. Even Delta-Matroids and the Complexity of Planar Boolean CSPs. SIAM, 2017, pp. 307–26, doi:10.1137/1.9781611974782.20. short: A. Kazda, V. Kolmogorov, M. Rolinek, in:, SIAM, 2017, pp. 307–326. conference: end_date: 2017-01019 location: Barcelona, Spain name: 'SODA: Symposium on Discrete Algorithms' start_date: 2017-01-16 date_created: 2018-12-11T11:50:38Z date_published: 2017-01-01T00:00:00Z date_updated: 2023-09-20T11:20:26Z day: '01' department: - _id: VlKo doi: 10.1137/1.9781611974782.20 ec_funded: 1 external_id: isi: - '000426965800020' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1602.03124 month: '01' oa: 1 oa_version: Submitted Version page: 307 - 326 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_identifier: isbn: - 978-161197478-2 publication_status: published publisher: SIAM publist_id: '6159' quality_controlled: '1' related_material: record: - id: '6032' relation: later_version status: public status: public title: Even delta-matroids and the complexity of planar Boolean CSPs type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2017' ... --- _id: '916' abstract: - lang: eng text: We study the quadratic assignment problem, in computer vision also known as graph matching. Two leading solvers for this problem optimize the Lagrange decomposition duals with sub-gradient and dual ascent (also known as message passing) updates. We explore this direction further and propose several additional Lagrangean relaxations of the graph matching problem along with corresponding algorithms, which are all based on a common dual ascent framework. Our extensive empirical evaluation gives several theoretical insights and suggests a new state-of-the-art anytime solver for the considered problem. Our improvement over state-of-the-art is particularly visible on a new dataset with large-scale sparse problem instances containing more than 500 graph nodes each. article_processing_charge: No author: - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Carsten full_name: Rother, Carsten last_name: Rother - first_name: Carsten full_name: Abu Alhaija, Carsten last_name: Abu Alhaija - first_name: Dagmar full_name: Kainmueller, Dagmar last_name: Kainmueller - first_name: Bogdan full_name: Savchynskyy, Bogdan last_name: Savchynskyy citation: ama: 'Swoboda P, Rother C, Abu Alhaija C, Kainmueller D, Savchynskyy B. A study of lagrangean decompositions and dual ascent solvers for graph matching. In: Vol 2017. IEEE; 2017:7062-7071. doi:10.1109/CVPR.2017.747' apa: 'Swoboda, P., Rother, C., Abu Alhaija, C., Kainmueller, D., & Savchynskyy, B. (2017). A study of lagrangean decompositions and dual ascent solvers for graph matching (Vol. 2017, pp. 7062–7071). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.747' chicago: Swoboda, Paul, Carsten Rother, Carsten Abu Alhaija, Dagmar Kainmueller, and Bogdan Savchynskyy. “A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching,” 2017:7062–71. IEEE, 2017. https://doi.org/10.1109/CVPR.2017.747. ieee: 'P. Swoboda, C. Rother, C. Abu Alhaija, D. Kainmueller, and B. Savchynskyy, “A study of lagrangean decompositions and dual ascent solvers for graph matching,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 7062–7071.' ista: 'Swoboda P, Rother C, Abu Alhaija C, Kainmueller D, Savchynskyy B. 2017. A study of lagrangean decompositions and dual ascent solvers for graph matching. CVPR: Computer Vision and Pattern Recognition vol. 2017, 7062–7071.' mla: Swoboda, Paul, et al. A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching. Vol. 2017, IEEE, 2017, pp. 7062–71, doi:10.1109/CVPR.2017.747. short: P. Swoboda, C. Rother, C. Abu Alhaija, D. Kainmueller, B. Savchynskyy, in:, IEEE, 2017, pp. 7062–7071. conference: end_date: 2017-07-26 location: Honolulu, HA, United States name: 'CVPR: Computer Vision and Pattern Recognition' start_date: 2017-07-21 date_created: 2018-12-11T11:49:11Z date_published: 2017-01-01T00:00:00Z date_updated: 2023-09-26T15:41:40Z day: '01' ddc: - '000' department: - _id: VlKo doi: 10.1109/CVPR.2017.747 ec_funded: 1 external_id: isi: - '000418371407018' file: - access_level: open_access checksum: e38a2740daad1ea178465843b5072906 content_type: application/pdf creator: dernst date_created: 2019-01-18T12:49:38Z date_updated: 2020-07-14T12:48:15Z file_id: '5848' file_name: 2017_CVPR_Swoboda2.pdf file_size: 944332 relation: main_file file_date_updated: 2020-07-14T12:48:15Z has_accepted_license: '1' intvolume: ' 2017' isi: 1 language: - iso: eng month: '01' oa: 1 oa_version: Submitted Version page: 7062-7071 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_identifier: isbn: - 978-153860457-1 publication_status: published publisher: IEEE publist_id: '6525' quality_controlled: '1' scopus_import: '1' status: public title: A study of lagrangean decompositions and dual ascent solvers for graph matching type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2017 year: '2017' ... --- _id: '915' abstract: - lang: eng text: We propose a dual decomposition and linear program relaxation of the NP-hard minimum cost multicut problem. Unlike other polyhedral relaxations of the multicut polytope, it is amenable to efficient optimization by message passing. Like other polyhedral relaxations, it can be tightened efficiently by cutting planes. We define an algorithm that alternates between message passing and efficient separation of cycle- and odd-wheel inequalities. This algorithm is more efficient than state-of-the-art algorithms based on linear programming, including algorithms written in the framework of leading commercial software, as we show in experiments with large instances of the problem from applications in computer vision, biomedical image analysis and data mining. article_processing_charge: No author: - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Bjoern full_name: Andres, Bjoern last_name: Andres citation: ama: 'Swoboda P, Andres B. A message passing algorithm for the minimum cost multicut problem. In: Vol 2017. IEEE; 2017:4990-4999. doi:10.1109/CVPR.2017.530' apa: 'Swoboda, P., & Andres, B. (2017). A message passing algorithm for the minimum cost multicut problem (Vol. 2017, pp. 4990–4999). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.530' chicago: Swoboda, Paul, and Bjoern Andres. “A Message Passing Algorithm for the Minimum Cost Multicut Problem,” 2017:4990–99. IEEE, 2017. https://doi.org/10.1109/CVPR.2017.530. ieee: 'P. Swoboda and B. Andres, “A message passing algorithm for the minimum cost multicut problem,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 4990–4999.' ista: 'Swoboda P, Andres B. 2017. A message passing algorithm for the minimum cost multicut problem. CVPR: Computer Vision and Pattern Recognition vol. 2017, 4990–4999.' mla: Swoboda, Paul, and Bjoern Andres. A Message Passing Algorithm for the Minimum Cost Multicut Problem. Vol. 2017, IEEE, 2017, pp. 4990–99, doi:10.1109/CVPR.2017.530. short: P. Swoboda, B. Andres, in:, IEEE, 2017, pp. 4990–4999. conference: end_date: 2017-07-26 location: Honolulu, HA, United States name: 'CVPR: Computer Vision and Pattern Recognition' start_date: 2017-07-21 date_created: 2018-12-11T11:49:11Z date_published: 2017-07-01T00:00:00Z date_updated: 2023-09-26T15:43:27Z day: '01' ddc: - '000' department: - _id: VlKo doi: 10.1109/CVPR.2017.530 ec_funded: 1 external_id: isi: - '000418371405009' file: - access_level: open_access checksum: 7e51dacefa693574581a32da3eff63dc content_type: application/pdf creator: dernst date_created: 2019-01-18T12:52:46Z date_updated: 2020-07-14T12:48:15Z file_id: '5849' file_name: Swoboda_A_Message_Passing_CVPR_2017_paper.pdf file_size: 883264 relation: main_file file_date_updated: 2020-07-14T12:48:15Z has_accepted_license: '1' intvolume: ' 2017' isi: 1 language: - iso: eng month: '07' oa: 1 oa_version: Submitted Version page: 4990-4999 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_identifier: isbn: - 978-153860457-1 publication_status: published publisher: IEEE publist_id: '6526' quality_controlled: '1' scopus_import: '1' status: public title: A message passing algorithm for the minimum cost multicut problem type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2017 year: '2017' ... --- _id: '917' abstract: - lang: eng text: We propose a general dual ascent framework for Lagrangean decomposition of combinatorial problems. Although methods of this type have shown their efficiency for a number of problems, so far there was no general algorithm applicable to multiple problem types. In this work, we propose such a general algorithm. It depends on several parameters, which can be used to optimize its performance in each particular setting. We demonstrate efficacy of our method on graph matching and multicut problems, where it outperforms state-of-the-art solvers including those based on subgradient optimization and off-the-shelf linear programming solvers. article_processing_charge: No author: - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Jan full_name: Kuske, Jan last_name: Kuske - first_name: Bogdan full_name: Savchynskyy, Bogdan last_name: Savchynskyy citation: ama: 'Swoboda P, Kuske J, Savchynskyy B. A dual ascent framework for Lagrangean decomposition of combinatorial problems. In: Vol 2017. IEEE; 2017:4950-4960. doi:10.1109/CVPR.2017.526' apa: 'Swoboda, P., Kuske, J., & Savchynskyy, B. (2017). A dual ascent framework for Lagrangean decomposition of combinatorial problems (Vol. 2017, pp. 4950–4960). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.526' chicago: Swoboda, Paul, Jan Kuske, and Bogdan Savchynskyy. “A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems,” 2017:4950–60. IEEE, 2017. https://doi.org/10.1109/CVPR.2017.526. ieee: 'P. Swoboda, J. Kuske, and B. Savchynskyy, “A dual ascent framework for Lagrangean decomposition of combinatorial problems,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 4950–4960.' ista: 'Swoboda P, Kuske J, Savchynskyy B. 2017. A dual ascent framework for Lagrangean decomposition of combinatorial problems. CVPR: Computer Vision and Pattern Recognition vol. 2017, 4950–4960.' mla: Swoboda, Paul, et al. A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems. Vol. 2017, IEEE, 2017, pp. 4950–60, doi:10.1109/CVPR.2017.526. short: P. Swoboda, J. Kuske, B. Savchynskyy, in:, IEEE, 2017, pp. 4950–4960. conference: end_date: 2017-07-26 location: Honolulu, HA, United States name: 'CVPR: Computer Vision and Pattern Recognition' start_date: 2017-07-21 date_created: 2018-12-11T11:49:11Z date_published: 2017-07-01T00:00:00Z date_updated: 2023-09-26T15:41:11Z day: '01' ddc: - '000' department: - _id: VlKo doi: 10.1109/CVPR.2017.526 ec_funded: 1 external_id: isi: - '000418371405005' file: - access_level: open_access checksum: 72fd291046bd8e5717961bd68f6b6f03 content_type: application/pdf creator: dernst date_created: 2019-01-18T12:45:55Z date_updated: 2020-07-14T12:48:15Z file_id: '5847' file_name: 2017_CVPR_Swoboda.pdf file_size: 898652 relation: main_file file_date_updated: 2020-07-14T12:48:15Z has_accepted_license: '1' intvolume: ' 2017' isi: 1 language: - iso: eng month: '07' oa: 1 oa_version: Submitted Version page: 4950-4960 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_identifier: isbn: - 978-153860457-1 publication_status: published publisher: IEEE publist_id: '6524' quality_controlled: '1' scopus_import: '1' status: public title: A dual ascent framework for Lagrangean decomposition of combinatorial problems type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2017 year: '2017' ... --- _id: '274' abstract: - lang: eng text: We consider the problem of estimating the partition function Z(β)=∑xexp(−β(H(x)) of a Gibbs distribution with a Hamilton H(⋅), or more precisely the logarithm of the ratio q=lnZ(0)/Z(β). It has been recently shown how to approximate q with high probability assuming the existence of an oracle that produces samples from the Gibbs distribution for a given parameter value in [0,β]. The current best known approach due to Huber [9] uses O(qlnn⋅[lnq+lnlnn+ε−2]) oracle calls on average where ε is the desired accuracy of approximation and H(⋅) is assumed to lie in {0}∪[1,n]. We improve the complexity to O(qlnn⋅ε−2) oracle calls. We also show that the same complexity can be achieved if exact oracles are replaced with approximate sampling oracles that are within O(ε2qlnn) variation distance from exact oracles. Finally, we prove a lower bound of Ω(q⋅ε−2) oracle calls under a natural model of computation. article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Kolmogorov V. A faster approximation algorithm for the Gibbs partition function. In: Proceedings of the 31st Conference On Learning Theory. Vol 75. ML Research Press; 2017:228-249.' apa: Kolmogorov, V. (2017). A faster approximation algorithm for the Gibbs partition function. In Proceedings of the 31st Conference On Learning Theory (Vol. 75, pp. 228–249). ML Research Press. chicago: Kolmogorov, Vladimir. “A Faster Approximation Algorithm for the Gibbs Partition Function.” In Proceedings of the 31st Conference On Learning Theory, 75:228–49. ML Research Press, 2017. ieee: V. Kolmogorov, “A faster approximation algorithm for the Gibbs partition function,” in Proceedings of the 31st Conference On Learning Theory, 2017, vol. 75, pp. 228–249. ista: 'Kolmogorov V. 2017. A faster approximation algorithm for the Gibbs partition function. Proceedings of the 31st Conference On Learning Theory. COLT: Annual Conference on Learning Theory vol. 75, 228–249.' mla: Kolmogorov, Vladimir. “A Faster Approximation Algorithm for the Gibbs Partition Function.” Proceedings of the 31st Conference On Learning Theory, vol. 75, ML Research Press, 2017, pp. 228–49. short: V. Kolmogorov, in:, Proceedings of the 31st Conference On Learning Theory, ML Research Press, 2017, pp. 228–249. conference: end_date: 2018-07-09 name: 'COLT: Annual Conference on Learning Theory ' start_date: 2018-07-06 date_created: 2018-12-11T11:45:33Z date_published: 2017-12-27T00:00:00Z date_updated: 2023-10-17T12:32:13Z day: '27' ddc: - '510' department: - _id: VlKo ec_funded: 1 external_id: arxiv: - '1608.04223' file: - access_level: open_access checksum: 89db06a0e8083524449cb59b56bf4e5b content_type: application/pdf creator: dernst date_created: 2020-05-12T09:23:27Z date_updated: 2020-07-14T12:45:45Z file_id: '7820' file_name: 2018_PMLR_Kolmogorov.pdf file_size: 408974 relation: main_file file_date_updated: 2020-07-14T12:45:45Z has_accepted_license: '1' intvolume: ' 75' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: 228-249 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Proceedings of the 31st Conference On Learning Theory publication_status: published publisher: ML Research Press publist_id: '7628' quality_controlled: '1' status: public title: A faster approximation algorithm for the Gibbs partition function tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 75 year: '2017' ... --- _id: '5561' abstract: - lang: eng text: 'Graph matching problems as described in "Active Graph Matching for Automatic Joint Segmentation and Annotation of C. Elegans." by Kainmueller, Dagmar and Jug, Florian and Rother, Carsten and Myers, Gene, MICCAI 2014. Problems are in OpenGM2 hdf5 format (see http://hciweb2.iwr.uni-heidelberg.de/opengm/) and a custom text format used by the feature matching solver described in "Feature Correspondence via Graph Matching: Models and Global Optimization." by Lorenzo Torresani, Vladimir Kolmogorov and Carsten Rother, ECCV 2008, code at http://pub.ist.ac.at/~vnk/software/GraphMatching-v1.02.src.zip. ' acknowledgement: We thank Vladimir Kolmogorov and Stephan Saalfeld forinspiring discussions. article_processing_charge: No author: - first_name: Dagmar full_name: Kainmueller, Dagmar last_name: Kainmueller - first_name: Florian full_name: Jug, Florian last_name: Jug - first_name: Carsten full_name: Rother, Carsten last_name: Rother - first_name: Gene full_name: Meyers, Gene last_name: Meyers citation: ama: Kainmueller D, Jug F, Rother C, Meyers G. Graph matching problems for annotating C. Elegans. 2017. doi:10.15479/AT:ISTA:57 apa: Kainmueller, D., Jug, F., Rother, C., & Meyers, G. (2017). Graph matching problems for annotating C. Elegans. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:57 chicago: Kainmueller, Dagmar, Florian Jug, Carsten Rother, and Gene Meyers. “Graph Matching Problems for Annotating C. Elegans.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:57. ieee: D. Kainmueller, F. Jug, C. Rother, and G. Meyers, “Graph matching problems for annotating C. Elegans.” Institute of Science and Technology Austria, 2017. ista: Kainmueller D, Jug F, Rother C, Meyers G. 2017. Graph matching problems for annotating C. Elegans, Institute of Science and Technology Austria, 10.15479/AT:ISTA:57. mla: Kainmueller, Dagmar, et al. Graph Matching Problems for Annotating C. Elegans. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:57. short: D. Kainmueller, F. Jug, C. Rother, G. Meyers, (2017). datarep_id: '57' date_created: 2018-12-12T12:31:32Z date_published: 2017-02-13T00:00:00Z date_updated: 2024-02-21T13:46:31Z day: '13' ddc: - '000' department: - _id: VlKo doi: 10.15479/AT:ISTA:57 file: - access_level: open_access checksum: 3dc3e1306a66028a34181ebef2923139 content_type: application/zip creator: system date_created: 2018-12-12T13:02:54Z date_updated: 2020-07-14T12:47:03Z file_id: '5614' file_name: IST-2017-57-v1+1_wormMatchingProblems.zip file_size: 327042819 relation: main_file file_date_updated: 2020-07-14T12:47:03Z has_accepted_license: '1' keyword: - graph matching - feature matching - QAP - MAP-inference month: '02' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria status: public title: Graph matching problems for annotating C. Elegans tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2017' ... --- _id: '1231' abstract: - lang: eng text: 'We study the time-and memory-complexities of the problem of computing labels of (multiple) randomly selected challenge-nodes in a directed acyclic graph. The w-bit label of a node is the hash of the labels of its parents, and the hash function is modeled as a random oracle. Specific instances of this problem underlie both proofs of space [Dziembowski et al. CRYPTO’15] as well as popular memory-hard functions like scrypt. As our main tool, we introduce the new notion of a probabilistic parallel entangled pebbling game, a new type of combinatorial pebbling game on a graph, which is closely related to the labeling game on the same graph. As a first application of our framework, we prove that for scrypt, when the underlying hash function is invoked n times, the cumulative memory complexity (CMC) (a notion recently introduced by Alwen and Serbinenko (STOC’15) to capture amortized memory-hardness for parallel adversaries) is at least Ω(w · (n/ log(n))2). This bound holds for adversaries that can store many natural functions of the labels (e.g., linear combinations), but still not arbitrary functions thereof. We then introduce and study a combinatorial quantity, and show how a sufficiently small upper bound on it (which we conjecture) extends our CMC bound for scrypt to hold against arbitrary adversaries. We also show that such an upper bound solves the main open problem for proofs-of-space protocols: namely, establishing that the time complexity of computing the label of a random node in a graph on n nodes (given an initial kw-bit state) reduces tightly to the time complexity for black pebbling on the same graph (given an initial k-node pebbling).' acknowledgement: "Joël Alwen, Chethan Kamath, and Krzysztof Pietrzak’s research is partially supported by an ERC starting grant (259668-PSPC). Vladimir Kolmogorov is partially supported by an ERC consolidator grant (616160-DOICV). Binyi Chen was partially supported by NSF grants CNS-1423566 and CNS-1514526, and a gift from the Gareatis Foundation. Stefano Tessaro was partially supported by NSF grants CNS-1423566, CNS-1528178, a Hellman Fellowship, and the Glen and Susanne Culler Chair.\r\n\r\nThis work was done in part while the authors were visiting the Simons Institute for the Theory of Computing, supported by the Simons Foundation and by the DIMACS/Simons Collaboration in Cryptography through NSF grant CNS-1523467." alternative_title: - LNCS author: - first_name: Joel F full_name: Alwen, Joel F id: 2A8DFA8C-F248-11E8-B48F-1D18A9856A87 last_name: Alwen - first_name: Binyi full_name: Chen, Binyi last_name: Chen - first_name: Chethan full_name: Kamath Hosdurg, Chethan id: 4BD3F30E-F248-11E8-B48F-1D18A9856A87 last_name: Kamath Hosdurg - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Krzysztof Z full_name: Pietrzak, Krzysztof Z id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87 last_name: Pietrzak orcid: 0000-0002-9139-1654 - first_name: Stefano full_name: Tessaro, Stefano last_name: Tessaro citation: ama: 'Alwen JF, Chen B, Kamath Hosdurg C, Kolmogorov V, Pietrzak KZ, Tessaro S. On the complexity of scrypt and proofs of space in the parallel random oracle model. In: Vol 9666. Springer; 2016:358-387. doi:10.1007/978-3-662-49896-5_13' apa: 'Alwen, J. F., Chen, B., Kamath Hosdurg, C., Kolmogorov, V., Pietrzak, K. Z., & Tessaro, S. (2016). On the complexity of scrypt and proofs of space in the parallel random oracle model (Vol. 9666, pp. 358–387). Presented at the EUROCRYPT: Theory and Applications of Cryptographic Techniques, Vienna, Austria: Springer. https://doi.org/10.1007/978-3-662-49896-5_13' chicago: Alwen, Joel F, Binyi Chen, Chethan Kamath Hosdurg, Vladimir Kolmogorov, Krzysztof Z Pietrzak, and Stefano Tessaro. “On the Complexity of Scrypt and Proofs of Space in the Parallel Random Oracle Model,” 9666:358–87. Springer, 2016. https://doi.org/10.1007/978-3-662-49896-5_13. ieee: 'J. F. Alwen, B. Chen, C. Kamath Hosdurg, V. Kolmogorov, K. Z. Pietrzak, and S. Tessaro, “On the complexity of scrypt and proofs of space in the parallel random oracle model,” presented at the EUROCRYPT: Theory and Applications of Cryptographic Techniques, Vienna, Austria, 2016, vol. 9666, pp. 358–387.' ista: 'Alwen JF, Chen B, Kamath Hosdurg C, Kolmogorov V, Pietrzak KZ, Tessaro S. 2016. On the complexity of scrypt and proofs of space in the parallel random oracle model. EUROCRYPT: Theory and Applications of Cryptographic Techniques, LNCS, vol. 9666, 358–387.' mla: Alwen, Joel F., et al. On the Complexity of Scrypt and Proofs of Space in the Parallel Random Oracle Model. Vol. 9666, Springer, 2016, pp. 358–87, doi:10.1007/978-3-662-49896-5_13. short: J.F. Alwen, B. Chen, C. Kamath Hosdurg, V. Kolmogorov, K.Z. Pietrzak, S. Tessaro, in:, Springer, 2016, pp. 358–387. conference: end_date: 2016-05-12 location: Vienna, Austria name: 'EUROCRYPT: Theory and Applications of Cryptographic Techniques' start_date: 2016-05-08 date_created: 2018-12-11T11:50:51Z date_published: 2016-04-28T00:00:00Z date_updated: 2021-01-12T06:49:15Z day: '28' department: - _id: KrPi - _id: VlKo doi: 10.1007/978-3-662-49896-5_13 ec_funded: 1 intvolume: ' 9666' language: - iso: eng main_file_link: - open_access: '1' url: https://eprint.iacr.org/2016/100 month: '04' oa: 1 oa_version: Submitted Version page: 358 - 387 project: - _id: 258C570E-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '259668' name: Provable Security for Physical Cryptography - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_status: published publisher: Springer publist_id: '6103' quality_controlled: '1' scopus_import: 1 status: public title: On the complexity of scrypt and proofs of space in the parallel random oracle model type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 9666 year: '2016' ... --- _id: '1353' abstract: - lang: eng text: We characterize absorption in finite idempotent algebras by means of Jónsson absorption and cube term blockers. As an application we show that it is decidable whether a given subset is an absorbing subuniverse of an algebra given by the tables of its basic operations. acknowledgement: 'Libor Barto and Alexandr Kazda were supported by the the Grant Agency of the Czech Republic, grant GACR 13-01832S. ' author: - first_name: Libor full_name: Barto, Libor last_name: Barto - first_name: Alexandr full_name: Kazda, Alexandr id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87 last_name: Kazda citation: ama: Barto L, Kazda A. Deciding absorption. International Journal of Algebra and Computation. 2016;26(5):1033-1060. doi:10.1142/S0218196716500430 apa: Barto, L., & Kazda, A. (2016). Deciding absorption. International Journal of Algebra and Computation. World Scientific Publishing. https://doi.org/10.1142/S0218196716500430 chicago: Barto, Libor, and Alexandr Kazda. “Deciding Absorption.” International Journal of Algebra and Computation. World Scientific Publishing, 2016. https://doi.org/10.1142/S0218196716500430. ieee: L. Barto and A. Kazda, “Deciding absorption,” International Journal of Algebra and Computation, vol. 26, no. 5. World Scientific Publishing, pp. 1033–1060, 2016. ista: Barto L, Kazda A. 2016. Deciding absorption. International Journal of Algebra and Computation. 26(5), 1033–1060. mla: Barto, Libor, and Alexandr Kazda. “Deciding Absorption.” International Journal of Algebra and Computation, vol. 26, no. 5, World Scientific Publishing, 2016, pp. 1033–60, doi:10.1142/S0218196716500430. short: L. Barto, A. Kazda, International Journal of Algebra and Computation 26 (2016) 1033–1060. date_created: 2018-12-11T11:51:32Z date_published: 2016-07-20T00:00:00Z date_updated: 2021-01-12T06:50:06Z day: '20' department: - _id: VlKo doi: 10.1142/S0218196716500430 intvolume: ' 26' issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1512.07009 month: '07' oa: 1 oa_version: Preprint page: 1033 - 1060 publication: International Journal of Algebra and Computation publication_status: published publisher: World Scientific Publishing publist_id: '5893' quality_controlled: '1' scopus_import: 1 status: public title: Deciding absorption type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 26 year: '2016' ... --- _id: '1377' abstract: - lang: eng text: We consider the problem of minimizing the continuous valued total variation subject to different unary terms on trees and propose fast direct algorithms based on dynamic programming to solve these problems. We treat both the convex and the nonconvex case and derive worst-case complexities that are equal to or better than existing methods. We show applications to total variation based two dimensional image processing and computer vision problems based on a Lagrangian decomposition approach. The resulting algorithms are very effcient, offer a high degree of parallelism, and come along with memory requirements which are only in the order of the number of image pixels. author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Thomas full_name: Pock, Thomas last_name: Pock - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: Kolmogorov V, Pock T, Rolinek M. Total variation on a tree. SIAM Journal on Imaging Sciences. 2016;9(2):605-636. doi:10.1137/15M1010257 apa: Kolmogorov, V., Pock, T., & Rolinek, M. (2016). Total variation on a tree. SIAM Journal on Imaging Sciences. Society for Industrial and Applied Mathematics . https://doi.org/10.1137/15M1010257 chicago: Kolmogorov, Vladimir, Thomas Pock, and Michal Rolinek. “Total Variation on a Tree.” SIAM Journal on Imaging Sciences. Society for Industrial and Applied Mathematics , 2016. https://doi.org/10.1137/15M1010257. ieee: V. Kolmogorov, T. Pock, and M. Rolinek, “Total variation on a tree,” SIAM Journal on Imaging Sciences, vol. 9, no. 2. Society for Industrial and Applied Mathematics , pp. 605–636, 2016. ista: Kolmogorov V, Pock T, Rolinek M. 2016. Total variation on a tree. SIAM Journal on Imaging Sciences. 9(2), 605–636. mla: Kolmogorov, Vladimir, et al. “Total Variation on a Tree.” SIAM Journal on Imaging Sciences, vol. 9, no. 2, Society for Industrial and Applied Mathematics , 2016, pp. 605–36, doi:10.1137/15M1010257. short: V. Kolmogorov, T. Pock, M. Rolinek, SIAM Journal on Imaging Sciences 9 (2016) 605–636. date_created: 2018-12-11T11:51:40Z date_published: 2016-05-03T00:00:00Z date_updated: 2021-01-12T06:50:15Z day: '03' department: - _id: VlKo doi: 10.1137/15M1010257 ec_funded: 1 intvolume: ' 9' issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1502.07770 month: '05' oa: 1 oa_version: Preprint page: 605 - 636 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: SIAM Journal on Imaging Sciences publication_status: published publisher: 'Society for Industrial and Applied Mathematics ' publist_id: '5834' quality_controlled: '1' scopus_import: 1 status: public title: Total variation on a tree type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 9 year: '2016' ... --- _id: '1612' abstract: - lang: eng text: We prove that whenever A is a 3-conservative relational structure with only binary and unary relations,then the algebra of polymorphisms of A either has no Taylor operation (i.e.,CSP(A)is NP-complete),or it generates an SD(∧) variety (i.e.,CSP(A)has bounded width). author: - first_name: Alexandr full_name: Kazda, Alexandr id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87 last_name: Kazda citation: ama: Kazda A. CSP for binary conservative relational structures. Algebra Universalis. 2016;75(1):75-84. doi:10.1007/s00012-015-0358-8 apa: Kazda, A. (2016). CSP for binary conservative relational structures. Algebra Universalis. Springer. https://doi.org/10.1007/s00012-015-0358-8 chicago: Kazda, Alexandr. “CSP for Binary Conservative Relational Structures.” Algebra Universalis. Springer, 2016. https://doi.org/10.1007/s00012-015-0358-8. ieee: A. Kazda, “CSP for binary conservative relational structures,” Algebra Universalis, vol. 75, no. 1. Springer, pp. 75–84, 2016. ista: Kazda A. 2016. CSP for binary conservative relational structures. Algebra Universalis. 75(1), 75–84. mla: Kazda, Alexandr. “CSP for Binary Conservative Relational Structures.” Algebra Universalis, vol. 75, no. 1, Springer, 2016, pp. 75–84, doi:10.1007/s00012-015-0358-8. short: A. Kazda, Algebra Universalis 75 (2016) 75–84. date_created: 2018-12-11T11:53:01Z date_published: 2016-02-01T00:00:00Z date_updated: 2021-01-12T06:52:00Z day: '01' department: - _id: VlKo doi: 10.1007/s00012-015-0358-8 intvolume: ' 75' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1112.1099 month: '02' oa: 1 oa_version: Preprint page: 75 - 84 publication: Algebra Universalis publication_status: published publisher: Springer publist_id: '5554' quality_controlled: '1' scopus_import: 1 status: public title: CSP for binary conservative relational structures type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 75 year: '2016' ... --- _id: '1193' abstract: - lang: eng text: We consider the recent formulation of the Algorithmic Lovász Local Lemma [1], [2] for finding objects that avoid "bad features", or "flaws". It extends the Moser-Tardos resampling algorithm [3] to more general discrete spaces. At each step the method picks a flaw present in the current state and "resamples" it using a "resampling oracle" provided by the user. However, it is less flexible than the Moser-Tardos method since [1], [2] require a specific flaw selection rule, whereas [3] allows an arbitrary rule (and thus can potentially be implemented more efficiently). We formulate a new "commutativity" condition, and prove that it is sufficient for an arbitrary rule to work. It also enables an efficient parallelization under an additional assumption. We then show that existing resampling oracles for perfect matchings and permutations do satisfy this condition. Finally, we generalize the precondition in [2] (in the case of symmetric potential causality graphs). This unifies special cases that previously were treated separately. acknowledgement: European Unions Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no 616160 article_number: '7782993' article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Kolmogorov V. Commutativity in the algorithmic Lovasz local lemma. In: Proceedings - Annual IEEE Symposium on Foundations of Computer Science. Vol 2016-December. IEEE; 2016. doi:10.1109/FOCS.2016.88' apa: 'Kolmogorov, V. (2016). Commutativity in the algorithmic Lovasz local lemma. In Proceedings - Annual IEEE Symposium on Foundations of Computer Science (Vol. 2016–December). New Brunswick, NJ, USA : IEEE. https://doi.org/10.1109/FOCS.2016.88' chicago: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovasz Local Lemma.” In Proceedings - Annual IEEE Symposium on Foundations of Computer Science, Vol. 2016–December. IEEE, 2016. https://doi.org/10.1109/FOCS.2016.88. ieee: V. Kolmogorov, “Commutativity in the algorithmic Lovasz local lemma,” in Proceedings - Annual IEEE Symposium on Foundations of Computer Science, New Brunswick, NJ, USA , 2016, vol. 2016–December. ista: 'Kolmogorov V. 2016. Commutativity in the algorithmic Lovasz local lemma. Proceedings - Annual IEEE Symposium on Foundations of Computer Science. FOCS: Foundations of Computer Science vol. 2016–December, 7782993.' mla: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovasz Local Lemma.” Proceedings - Annual IEEE Symposium on Foundations of Computer Science, vol. 2016–December, 7782993, IEEE, 2016, doi:10.1109/FOCS.2016.88. short: V. Kolmogorov, in:, Proceedings - Annual IEEE Symposium on Foundations of Computer Science, IEEE, 2016. conference: end_date: 2016-09-11 location: 'New Brunswick, NJ, USA ' name: 'FOCS: Foundations of Computer Science' start_date: 2016-09-09 date_created: 2018-12-11T11:50:38Z date_published: 2016-12-15T00:00:00Z date_updated: 2023-09-19T14:24:57Z day: '15' department: - _id: VlKo doi: 10.1109/FOCS.2016.88 ec_funded: 1 external_id: arxiv: - '1506.08547' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1506.08547v7 month: '12' oa: 1 oa_version: Preprint project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Proceedings - Annual IEEE Symposium on Foundations of Computer Science publication_status: published publisher: IEEE publist_id: '6158' quality_controlled: '1' related_material: record: - id: '5975' relation: later_version status: public scopus_import: 1 status: public title: Commutativity in the algorithmic Lovasz local lemma type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2016-December year: '2016' ... --- _id: '1794' abstract: - lang: eng text: We consider Conditional random fields (CRFs) with pattern-based potentials defined on a chain. In this model the energy of a string (labeling) (Formula presented.) is the sum of terms over intervals [i, j] where each term is non-zero only if the substring (Formula presented.) equals a prespecified pattern w. Such CRFs can be naturally applied to many sequence tagging problems. We present efficient algorithms for the three standard inference tasks in a CRF, namely computing (i) the partition function, (ii) marginals, and (iii) computing the MAP. Their complexities are respectively (Formula presented.), (Formula presented.) and (Formula presented.) where L is the combined length of input patterns, (Formula presented.) is the maximum length of a pattern, and D is the input alphabet. This improves on the previous algorithms of Ye et al. (NIPS, 2009) whose complexities are respectively (Formula presented.), (Formula presented.) and (Formula presented.), where (Formula presented.) is the number of input patterns. In addition, we give an efficient algorithm for sampling, and revisit the case of MAP with non-positive weights. acknowledgement: This work has been partially supported by the European Research Council under the European Unions Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 616160. author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Rustem full_name: Takhanov, Rustem id: 2CCAC26C-F248-11E8-B48F-1D18A9856A87 last_name: Takhanov citation: ama: Kolmogorov V, Takhanov R. Inference algorithms for pattern-based CRFs on sequence data. Algorithmica. 2016;76(1):17-46. doi:10.1007/s00453-015-0017-7 apa: Kolmogorov, V., & Takhanov, R. (2016). Inference algorithms for pattern-based CRFs on sequence data. Algorithmica. Springer. https://doi.org/10.1007/s00453-015-0017-7 chicago: Kolmogorov, Vladimir, and Rustem Takhanov. “Inference Algorithms for Pattern-Based CRFs on Sequence Data.” Algorithmica. Springer, 2016. https://doi.org/10.1007/s00453-015-0017-7. ieee: V. Kolmogorov and R. Takhanov, “Inference algorithms for pattern-based CRFs on sequence data,” Algorithmica, vol. 76, no. 1. Springer, pp. 17–46, 2016. ista: Kolmogorov V, Takhanov R. 2016. Inference algorithms for pattern-based CRFs on sequence data. Algorithmica. 76(1), 17–46. mla: Kolmogorov, Vladimir, and Rustem Takhanov. “Inference Algorithms for Pattern-Based CRFs on Sequence Data.” Algorithmica, vol. 76, no. 1, Springer, 2016, pp. 17–46, doi:10.1007/s00453-015-0017-7. short: V. Kolmogorov, R. Takhanov, Algorithmica 76 (2016) 17–46. date_created: 2018-12-11T11:54:02Z date_published: 2016-09-01T00:00:00Z date_updated: 2023-10-17T09:51:31Z day: '01' department: - _id: VlKo doi: 10.1007/s00453-015-0017-7 ec_funded: 1 external_id: arxiv: - '1210.0508' intvolume: ' 76' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1210.0508 month: '09' oa: 1 oa_version: Preprint page: 17 - 46 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: Algorithmica publication_status: published publisher: Springer publist_id: '5316' quality_controlled: '1' related_material: record: - id: '2272' relation: earlier_version status: public scopus_import: 1 status: public title: Inference algorithms for pattern-based CRFs on sequence data type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 76 year: '2016' ... --- _id: '5557' abstract: - lang: eng text: "Small synthetic discrete tomography problems.\r\nSizes are 32x32, 64z64 and 256x256.\r\nProjection angles are 2, 4, and 6.\r\nNumber of labels are 3 and 5." article_processing_charge: No author: - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda citation: ama: Swoboda P. Synthetic discrete tomography problems. 2016. doi:10.15479/AT:ISTA:46 apa: Swoboda, P. (2016). Synthetic discrete tomography problems. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:46 chicago: Swoboda, Paul. “Synthetic Discrete Tomography Problems.” Institute of Science and Technology Austria, 2016. https://doi.org/10.15479/AT:ISTA:46. ieee: P. Swoboda, “Synthetic discrete tomography problems.” Institute of Science and Technology Austria, 2016. ista: Swoboda P. 2016. Synthetic discrete tomography problems, Institute of Science and Technology Austria, 10.15479/AT:ISTA:46. mla: Swoboda, Paul. Synthetic Discrete Tomography Problems. Institute of Science and Technology Austria, 2016, doi:10.15479/AT:ISTA:46. short: P. Swoboda, (2016). contributor: - contributor_type: data_collector first_name: Jan last_name: Kuske datarep_id: '46' date_created: 2018-12-12T12:31:31Z date_published: 2016-09-20T00:00:00Z date_updated: 2024-02-21T13:50:21Z day: '20' ddc: - '006' department: - _id: VlKo doi: 10.15479/AT:ISTA:46 file: - access_level: open_access checksum: aa5a16a0dc888da7186fb8fc45e88439 content_type: application/zip creator: system date_created: 2018-12-12T13:05:19Z date_updated: 2020-07-14T12:47:02Z file_id: '5645' file_name: IST-2016-46-v1+1_discrete_tomography_synthetic.zip file_size: 36058401 relation: main_file file_date_updated: 2020-07-14T12:47:02Z has_accepted_license: '1' keyword: - discrete tomography month: '09' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria status: public title: Synthetic discrete tomography problems tmp: image: /images/cc_0.png legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode name: Creative Commons Public Domain Dedication (CC0 1.0) short: CC0 (1.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2016' ... --- _id: '1636' abstract: - lang: eng text: "Constraint Satisfaction Problem (CSP) is a fundamental algorithmic problem that appears in many areas of Computer Science. It can be equivalently stated as computing a homomorphism R→ΓΓ between two relational structures, e.g. between two directed graphs. Analyzing its complexity has been a prominent research direction, especially for the fixed template CSPs where the right side ΓΓ is fixed and the left side R is unconstrained.\r\n\r\nFar fewer results are known for the hybrid setting that restricts both sides simultaneously. It assumes that R belongs to a certain class of relational structures (called a structural restriction in this paper). We study which structural restrictions are effective, i.e. there exists a fixed template ΓΓ (from a certain class of languages) for which the problem is tractable when R is restricted, and NP-hard otherwise. We provide a characterization for structural restrictions that are closed under inverse homomorphisms. The criterion is based on the chromatic number of a relational structure defined in this paper; it generalizes the standard chromatic number of a graph.\r\n\r\nAs our main tool, we use the algebraic machinery developed for fixed template CSPs. To apply it to our case, we introduce a new construction called a “lifted language”. We also give a characterization for structural restrictions corresponding to minor-closed families of graphs, extend results to certain Valued CSPs (namely conservative valued languages), and state implications for (valued) CSPs with ordered variables and for the maximum weight independent set problem on some restricted families of graphs." alternative_title: - LNCS article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek - first_name: Rustem full_name: Takhanov, Rustem last_name: Takhanov citation: ama: 'Kolmogorov V, Rolinek M, Takhanov R. Effectiveness of structural restrictions for hybrid CSPs. In: 26th International Symposium. Vol 9472. Springer Nature; 2015:566-577. doi:10.1007/978-3-662-48971-0_48' apa: 'Kolmogorov, V., Rolinek, M., & Takhanov, R. (2015). Effectiveness of structural restrictions for hybrid CSPs. In 26th International Symposium (Vol. 9472, pp. 566–577). Nagoya, Japan: Springer Nature. https://doi.org/10.1007/978-3-662-48971-0_48' chicago: Kolmogorov, Vladimir, Michal Rolinek, and Rustem Takhanov. “Effectiveness of Structural Restrictions for Hybrid CSPs.” In 26th International Symposium, 9472:566–77. Springer Nature, 2015. https://doi.org/10.1007/978-3-662-48971-0_48. ieee: V. Kolmogorov, M. Rolinek, and R. Takhanov, “Effectiveness of structural restrictions for hybrid CSPs,” in 26th International Symposium, Nagoya, Japan, 2015, vol. 9472, pp. 566–577. ista: 'Kolmogorov V, Rolinek M, Takhanov R. 2015. Effectiveness of structural restrictions for hybrid CSPs. 26th International Symposium. ISAAC: International Symposium on Algorithms and Computation, LNCS, vol. 9472, 566–577.' mla: Kolmogorov, Vladimir, et al. “Effectiveness of Structural Restrictions for Hybrid CSPs.” 26th International Symposium, vol. 9472, Springer Nature, 2015, pp. 566–77, doi:10.1007/978-3-662-48971-0_48. short: V. Kolmogorov, M. Rolinek, R. Takhanov, in:, 26th International Symposium, Springer Nature, 2015, pp. 566–577. conference: end_date: 2015-12-11 location: Nagoya, Japan name: 'ISAAC: International Symposium on Algorithms and Computation' start_date: 2015-12-09 date_created: 2018-12-11T11:53:10Z date_published: 2015-12-01T00:00:00Z date_updated: 2022-02-01T15:12:35Z day: '01' department: - _id: VlKo doi: 10.1007/978-3-662-48971-0_48 ec_funded: 1 external_id: arxiv: - '1504.07067' intvolume: ' 9472' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1504.07067 month: '12' oa: 1 oa_version: Preprint page: 566 - 577 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: 26th International Symposium publication_identifier: isbn: - 978-3-662-48970-3 publication_status: published publisher: Springer Nature publist_id: '5519' quality_controlled: '1' scopus_import: '1' status: public title: Effectiveness of structural restrictions for hybrid CSPs type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 9472 year: '2015' ... --- _id: '1841' abstract: - lang: eng text: We propose a new family of message passing techniques for MAP estimation in graphical models which we call Sequential Reweighted Message Passing (SRMP). Special cases include well-known techniques such as Min-Sum Diffusion (MSD) and a faster Sequential Tree-Reweighted Message Passing (TRW-S). Importantly, our derivation is simpler than the original derivation of TRW-S, and does not involve a decomposition into trees. This allows easy generalizations. The new family of algorithms can be viewed as a generalization of TRW-S from pairwise to higher-order graphical models. We test SRMP on several real-world problems with promising results. author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Kolmogorov V. A new look at reweighted message passing. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2015;37(5):919-930. doi:10.1109/TPAMI.2014.2363465 apa: Kolmogorov, V. (2015). A new look at reweighted message passing. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2014.2363465 chicago: Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2015. https://doi.org/10.1109/TPAMI.2014.2363465. ieee: V. Kolmogorov, “A new look at reweighted message passing,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 5. IEEE, pp. 919–930, 2015. ista: Kolmogorov V. 2015. A new look at reweighted message passing. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(5), 919–930. mla: Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 5, IEEE, 2015, pp. 919–30, doi:10.1109/TPAMI.2014.2363465. short: V. Kolmogorov, IEEE Transactions on Pattern Analysis and Machine Intelligence 37 (2015) 919–930. date_created: 2018-12-11T11:54:18Z date_published: 2015-05-01T00:00:00Z date_updated: 2021-01-12T06:53:33Z day: '01' department: - _id: VlKo doi: 10.1109/TPAMI.2014.2363465 ec_funded: 1 intvolume: ' 37' issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1309.5655 month: '05' oa: 1 oa_version: Preprint page: 919 - 930 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication: IEEE Transactions on Pattern Analysis and Machine Intelligence publication_status: published publisher: IEEE publist_id: '5261' quality_controlled: '1' scopus_import: 1 status: public title: A new look at reweighted message passing type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 37 year: '2015' ... --- _id: '1859' abstract: - lang: eng text: "Structural support vector machines (SSVMs) are amongst the best performing models for structured computer vision tasks, such as semantic image segmentation or human pose estimation. Training SSVMs, however, is computationally costly, because it requires repeated calls to a structured prediction subroutine (called \\emph{max-oracle}), which has to solve an optimization problem itself, e.g. a graph cut.\r\nIn this work, we introduce a new algorithm for SSVM training that is more efficient than earlier techniques when the max-oracle is computationally expensive, as it is frequently the case in computer vision tasks. The main idea is to (i) combine the recent stochastic Block-Coordinate Frank-Wolfe algorithm with efficient hyperplane caching, and (ii) use an automatic selection rule for deciding whether to call the exact max-oracle or to rely on an approximate one based on the cached hyperplanes.\r\nWe show experimentally that this strategy leads to faster convergence to the optimum with respect to the number of requires oracle calls, and that this translates into faster convergence with respect to the total runtime when the max-oracle is slow compared to the other steps of the algorithm. " author: - first_name: Neel full_name: Shah, Neel id: 31ABAF80-F248-11E8-B48F-1D18A9856A87 last_name: Shah - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Shah N, Kolmogorov V, Lampert C. A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle. In: IEEE; 2015:2737-2745. doi:10.1109/CVPR.2015.7298890' apa: 'Shah, N., Kolmogorov, V., & Lampert, C. (2015). A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle (pp. 2737–2745). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA: IEEE. https://doi.org/10.1109/CVPR.2015.7298890' chicago: Shah, Neel, Vladimir Kolmogorov, and Christoph Lampert. “A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly Max-Oracle,” 2737–45. IEEE, 2015. https://doi.org/10.1109/CVPR.2015.7298890. ieee: 'N. Shah, V. Kolmogorov, and C. Lampert, “A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle,” presented at the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp. 2737–2745.' ista: 'Shah N, Kolmogorov V, Lampert C. 2015. A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle. CVPR: Computer Vision and Pattern Recognition, 2737–2745.' mla: Shah, Neel, et al. A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly Max-Oracle. IEEE, 2015, pp. 2737–45, doi:10.1109/CVPR.2015.7298890. short: N. Shah, V. Kolmogorov, C. Lampert, in:, IEEE, 2015, pp. 2737–2745. conference: end_date: 2015-06-12 location: Boston, MA, USA name: 'CVPR: Computer Vision and Pattern Recognition' start_date: 2015-06-07 date_created: 2018-12-11T11:54:24Z date_published: 2015-06-01T00:00:00Z date_updated: 2021-01-12T06:53:40Z day: '01' department: - _id: VlKo - _id: ChLa doi: 10.1109/CVPR.2015.7298890 ec_funded: 1 language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1408.6804 month: '06' oa: 1 oa_version: Preprint page: 2737 - 2745 project: - _id: 2532554C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '308036' name: Lifelong Learning of Visual Scene Understanding - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_status: published publisher: IEEE publist_id: '5240' quality_controlled: '1' scopus_import: 1 status: public title: A multi-plane block-coordinate Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2015' ... --- _id: '1675' abstract: - lang: eng text: Proofs of work (PoW) have been suggested by Dwork and Naor (Crypto’92) as protection to a shared resource. The basic idea is to ask the service requestor to dedicate some non-trivial amount of computational work to every request. The original applications included prevention of spam and protection against denial of service attacks. More recently, PoWs have been used to prevent double spending in the Bitcoin digital currency system. In this work, we put forward an alternative concept for PoWs - so-called proofs of space (PoS), where a service requestor must dedicate a significant amount of disk space as opposed to computation. We construct secure PoS schemes in the random oracle model (with one additional mild assumption required for the proof to go through), using graphs with high “pebbling complexity” and Merkle hash-trees. We discuss some applications, including follow-up work where a decentralized digital currency scheme called Spacecoin is constructed that uses PoS (instead of wasteful PoW like in Bitcoin) to prevent double spending. The main technical contribution of this work is the construction of (directed, loop-free) graphs on N vertices with in-degree O(log logN) such that even if one places Θ(N) pebbles on the nodes of the graph, there’s a constant fraction of nodes that needs Θ(N) steps to be pebbled (where in every step one can put a pebble on a node if all its parents have a pebble). alternative_title: - LNCS author: - first_name: Stefan full_name: Dziembowski, Stefan last_name: Dziembowski - first_name: Sebastian full_name: Faust, Sebastian last_name: Faust - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Krzysztof Z full_name: Pietrzak, Krzysztof Z id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87 last_name: Pietrzak orcid: 0000-0002-9139-1654 citation: ama: Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. Proofs of space. 2015;9216:585-605. doi:10.1007/978-3-662-48000-7_29 apa: 'Dziembowski, S., Faust, S., Kolmogorov, V., & Pietrzak, K. Z. (2015). Proofs of space. Presented at the CRYPTO: International Cryptology Conference, Santa Barbara, CA, United States: Springer. https://doi.org/10.1007/978-3-662-48000-7_29' chicago: Dziembowski, Stefan, Sebastian Faust, Vladimir Kolmogorov, and Krzysztof Z Pietrzak. “Proofs of Space.” Lecture Notes in Computer Science. Springer, 2015. https://doi.org/10.1007/978-3-662-48000-7_29. ieee: S. Dziembowski, S. Faust, V. Kolmogorov, and K. Z. Pietrzak, “Proofs of space,” vol. 9216. Springer, pp. 585–605, 2015. ista: Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. 2015. Proofs of space. 9216, 585–605. mla: Dziembowski, Stefan, et al. Proofs of Space. Vol. 9216, Springer, 2015, pp. 585–605, doi:10.1007/978-3-662-48000-7_29. short: S. Dziembowski, S. Faust, V. Kolmogorov, K.Z. Pietrzak, 9216 (2015) 585–605. conference: end_date: 2015-08-20 location: Santa Barbara, CA, United States name: 'CRYPTO: International Cryptology Conference' start_date: 2015-08-16 date_created: 2018-12-11T11:53:24Z date_published: 2015-08-01T00:00:00Z date_updated: 2023-02-23T10:35:50Z day: '01' department: - _id: VlKo - _id: KrPi doi: 10.1007/978-3-662-48000-7_29 ec_funded: 1 intvolume: ' 9216' language: - iso: eng month: '08' oa_version: None page: 585 - 605 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' - _id: 258C570E-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '259668' name: Provable Security for Physical Cryptography publication_status: published publisher: Springer publist_id: '5474' pubrep_id: '671' quality_controlled: '1' related_material: record: - id: '2274' relation: earlier_version status: public scopus_import: 1 series_title: Lecture Notes in Computer Science status: public title: Proofs of space type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 9216 year: '2015' ... --- _id: '2271' abstract: - lang: eng text: "A class of valued constraint satisfaction problems (VCSPs) is characterised by a valued constraint language, a fixed set of cost functions on a finite domain. Finite-valued constraint languages contain functions that take on rational costs and general-valued constraint languages contain functions that take on rational or infinite costs. An instance of the problem is specified by a sum of functions from the language with the goal to minimise the sum. This framework includes and generalises well-studied constraint satisfaction problems (CSPs) and maximum constraint satisfaction problems (Max-CSPs).\r\nOur main result is a precise algebraic characterisation of valued constraint languages whose instances can be solved exactly by the basic linear programming relaxation (BLP). For a general-valued constraint language Γ, BLP is a decision procedure for Γ if and only if Γ admits a symmetric fractional polymorphism of every arity. For a finite-valued constraint language Γ, BLP is a decision procedure if and only if Γ admits a symmetric fractional polymorphism of some arity, or equivalently, if Γ admits a symmetric fractional polymorphism of arity 2.\r\nUsing these results, we obtain tractability of several novel and previously widely-open classes of VCSPs, including problems over valued constraint languages that are: (1) submodular on arbitrary lattices; (2) bisubmodular (also known as k-submodular) on arbitrary finite domains; (3) weakly (and hence strongly) tree-submodular on arbitrary trees. " author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Johan full_name: Thapper, Johan last_name: Thapper - first_name: Stanislav full_name: Živný, Stanislav last_name: Živný citation: ama: Kolmogorov V, Thapper J, Živný S. The power of linear programming for general-valued CSPs. SIAM Journal on Computing. 2015;44(1):1-36. doi:10.1137/130945648 apa: Kolmogorov, V., Thapper, J., & Živný, S. (2015). The power of linear programming for general-valued CSPs. SIAM Journal on Computing. SIAM. https://doi.org/10.1137/130945648 chicago: Kolmogorov, Vladimir, Johan Thapper, and Stanislav Živný. “The Power of Linear Programming for General-Valued CSPs.” SIAM Journal on Computing. SIAM, 2015. https://doi.org/10.1137/130945648. ieee: V. Kolmogorov, J. Thapper, and S. Živný, “The power of linear programming for general-valued CSPs,” SIAM Journal on Computing, vol. 44, no. 1. SIAM, pp. 1–36, 2015. ista: Kolmogorov V, Thapper J, Živný S. 2015. The power of linear programming for general-valued CSPs. SIAM Journal on Computing. 44(1), 1–36. mla: Kolmogorov, Vladimir, et al. “The Power of Linear Programming for General-Valued CSPs.” SIAM Journal on Computing, vol. 44, no. 1, SIAM, 2015, pp. 1–36, doi:10.1137/130945648. short: V. Kolmogorov, J. Thapper, S. Živný, SIAM Journal on Computing 44 (2015) 1–36. date_created: 2018-12-11T11:56:41Z date_published: 2015-02-01T00:00:00Z date_updated: 2023-02-23T10:46:30Z day: '01' department: - _id: VlKo doi: 10.1137/130945648 external_id: arxiv: - '1311.4219' intvolume: ' 44' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1311.4219 month: '02' oa: 1 oa_version: Preprint page: 1 - 36 publication: SIAM Journal on Computing publication_status: published publisher: SIAM publist_id: '4673' quality_controlled: '1' related_material: record: - id: '2518' relation: earlier_version status: public scopus_import: 1 status: public title: The power of linear programming for general-valued CSPs type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 44 year: '2015' ... --- _id: '1637' abstract: - lang: eng text: An instance of the Valued Constraint Satisfaction Problem (VCSP) is given by a finite set of variables, a finite domain of labels, and a sum of functions, each function depending on a subset of the variables. Each function can take finite values specifying costs of assignments of labels to its variables or the infinite value, which indicates an infeasible assignment. The goal is to find an assignment of labels to the variables that minimizes the sum. We study, assuming that P ≠ NP, how the complexity of this very general problem depends on the set of functions allowed in the instances, the so-called constraint language. The case when all allowed functions take values in {0, ∞} corresponds to ordinary CSPs, where one deals only with the feasibility issue and there is no optimization. This case is the subject of the Algebraic CSP Dichotomy Conjecture predicting for which constraint languages CSPs are tractable (i.e. solvable in polynomial time) and for which NP-hard. The case when all allowed functions take only finite values corresponds to finite-valued CSP, where the feasibility aspect is trivial and one deals only with the optimization issue. The complexity of finite-valued CSPs was fully classified by Thapper and Zivny. An algebraic necessary condition for tractability of a general-valued CSP with a fixed constraint language was recently given by Kozik and Ochremiak. As our main result, we prove that if a constraint language satisfies this algebraic necessary condition, and the feasibility CSP (i.e. the problem of deciding whether a given instance has a feasible solution) corresponding to the VCSP with this language is tractable, then the VCSP is tractable. The algorithm is a simple combination of the assumed algorithm for the feasibility CSP and the standard LP relaxation. As a corollary, we obtain that a dichotomy for ordinary CSPs would imply a dichotomy for general-valued CSPs. alternative_title: - 56th Annual Symposium on Foundations of Computer Science author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Andrei full_name: Krokhin, Andrei last_name: Krokhin - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: 'Kolmogorov V, Krokhin A, Rolinek M. The complexity of general-valued CSPs. In: IEEE; 2015:1246-1258. doi:10.1109/FOCS.2015.80' apa: 'Kolmogorov, V., Krokhin, A., & Rolinek, M. (2015). The complexity of general-valued CSPs (pp. 1246–1258). Presented at the FOCS: Foundations of Computer Science, Berkeley, CA, United States: IEEE. https://doi.org/10.1109/FOCS.2015.80' chicago: Kolmogorov, Vladimir, Andrei Krokhin, and Michal Rolinek. “The Complexity of General-Valued CSPs,” 1246–58. IEEE, 2015. https://doi.org/10.1109/FOCS.2015.80. ieee: 'V. Kolmogorov, A. Krokhin, and M. Rolinek, “The complexity of general-valued CSPs,” presented at the FOCS: Foundations of Computer Science, Berkeley, CA, United States, 2015, pp. 1246–1258.' ista: 'Kolmogorov V, Krokhin A, Rolinek M. 2015. The complexity of general-valued CSPs. FOCS: Foundations of Computer Science, 56th Annual Symposium on Foundations of Computer Science, , 1246–1258.' mla: Kolmogorov, Vladimir, et al. The Complexity of General-Valued CSPs. IEEE, 2015, pp. 1246–58, doi:10.1109/FOCS.2015.80. short: V. Kolmogorov, A. Krokhin, M. Rolinek, in:, IEEE, 2015, pp. 1246–1258. conference: end_date: 2015-10-20 location: Berkeley, CA, United States name: 'FOCS: Foundations of Computer Science' start_date: 2015-10-18 date_created: 2018-12-11T11:53:10Z date_published: 2015-12-01T00:00:00Z date_updated: 2023-02-23T12:44:26Z day: '01' department: - _id: VlKo doi: 10.1109/FOCS.2015.80 ec_funded: 1 language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1502.07327 month: '12' oa: 1 oa_version: Preprint page: 1246 - 1258 project: - _id: 25FBA906-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '616160' name: 'Discrete Optimization in Computer Vision: Theory and Practice' publication_status: published publisher: IEEE publist_id: '5518' quality_controlled: '1' related_material: record: - id: '644' relation: other status: public scopus_import: 1 status: public title: The complexity of general-valued CSPs type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2015' ... --- _id: '2275' abstract: - lang: eng text: "Energies with high-order non-submodular interactions have been shown to be very useful in vision due to their high modeling power. Optimization of such energies, however, is generally NP-hard. A naive approach that works for small problem instances is exhaustive search, that is, enumeration of all possible labelings of the underlying graph. We propose a general minimization approach for large graphs based on enumeration of labelings of certain small patches. \r\nThis partial enumeration technique reduces complex high-order energy formulations to pairwise Constraint Satisfaction Problems with unary costs (uCSP), which can be efficiently solved using standard methods like TRW-S. Our approach outperforms a number of existing state-of-the-art algorithms on well known difficult problems (e.g. curvature regularization, stereo, deconvolution); it gives near global minimum and better speed. \r\nOur main application of interest is curvature regularization. In the context of segmentation, our partial enumeration technique allows to evaluate curvature directly on small patches using a novel integral geometry approach.\r\n" author: - first_name: Carl full_name: Olsson, Carl last_name: Olsson - first_name: Johannes full_name: Ulen, Johannes last_name: Ulen - first_name: Yuri full_name: Boykov, Yuri last_name: Boykov - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Olsson C, Ulen J, Boykov Y, Kolmogorov V. Partial enumeration and curvature regularization. In: IEEE; 2014:2936-2943. doi:10.1109/ICCV.2013.365' apa: 'Olsson, C., Ulen, J., Boykov, Y., & Kolmogorov, V. (2014). Partial enumeration and curvature regularization (pp. 2936–2943). Presented at the ICCV: International Conference on Computer Vision, Sydney, Australia: IEEE. https://doi.org/10.1109/ICCV.2013.365' chicago: Olsson, Carl, Johannes Ulen, Yuri Boykov, and Vladimir Kolmogorov. “Partial Enumeration and Curvature Regularization,” 2936–43. IEEE, 2014. https://doi.org/10.1109/ICCV.2013.365. ieee: 'C. Olsson, J. Ulen, Y. Boykov, and V. Kolmogorov, “Partial enumeration and curvature regularization,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2014, pp. 2936–2943.' ista: 'Olsson C, Ulen J, Boykov Y, Kolmogorov V. 2014. Partial enumeration and curvature regularization. ICCV: International Conference on Computer Vision, 2936–2943.' mla: Olsson, Carl, et al. Partial Enumeration and Curvature Regularization. IEEE, 2014, pp. 2936–43, doi:10.1109/ICCV.2013.365. short: C. Olsson, J. Ulen, Y. Boykov, V. Kolmogorov, in:, IEEE, 2014, pp. 2936–2943. conference: end_date: 2013-12-08 location: Sydney, Australia name: 'ICCV: International Conference on Computer Vision' start_date: 2013-12-01 date_created: 2018-12-11T11:56:42Z date_published: 2014-03-03T00:00:00Z date_updated: 2021-01-12T06:56:28Z day: '03' ddc: - '000' department: - _id: VlKo doi: 10.1109/ICCV.2013.365 file: - access_level: open_access checksum: 4a74b5c92d6dcd2348c2c10ec8dd18bf content_type: application/pdf creator: system date_created: 2018-12-12T10:09:30Z date_updated: 2020-07-14T12:45:36Z file_id: '4754' file_name: IST-2016-566-v1+1_iccv13_part_enumeration.pdf file_size: 378601 relation: main_file file_date_updated: 2020-07-14T12:45:36Z has_accepted_license: '1' language: - iso: eng month: '03' oa: 1 oa_version: Submitted Version page: 2936 - 2943 publication_status: published publisher: IEEE publist_id: '4669' pubrep_id: '566' quality_controlled: '1' scopus_import: 1 status: public title: Partial enumeration and curvature regularization type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2014' ... --- _id: '7038' article_processing_charge: No author: - first_name: Kristóf full_name: Huszár, Kristóf id: 33C26278-F248-11E8-B48F-1D18A9856A87 last_name: Huszár orcid: 0000-0002-5445-5057 - first_name: Michal full_name: Rolinek, Michal id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87 last_name: Rolinek citation: ama: Huszár K, Rolinek M. Playful Math - An Introduction to Mathematical Games. IST Austria apa: Huszár, K., & Rolinek, M. (n.d.). Playful Math - An introduction to mathematical games. IST Austria. chicago: Huszár, Kristóf, and Michal Rolinek. Playful Math - An Introduction to Mathematical Games. IST Austria, n.d. ieee: K. Huszár and M. Rolinek, Playful Math - An introduction to mathematical games. IST Austria. ista: Huszár K, Rolinek M. Playful Math - An introduction to mathematical games, IST Austria, 5p. mla: Huszár, Kristóf, and Michal Rolinek. Playful Math - An Introduction to Mathematical Games. IST Austria. short: K. Huszár, M. Rolinek, Playful Math - An Introduction to Mathematical Games, IST Austria, n.d. date_created: 2019-11-18T15:57:05Z date_published: 2014-06-30T00:00:00Z date_updated: 2020-07-14T23:11:45Z day: '30' ddc: - '510' department: - _id: VlKo - _id: UlWa file: - access_level: open_access checksum: 2b94e5e1f4c3fe8ab89b12806276fb09 content_type: application/pdf creator: dernst date_created: 2019-11-18T15:57:51Z date_updated: 2020-07-14T12:47:48Z file_id: '7039' file_name: 2014_Playful_Math_Huszar.pdf file_size: 511233 relation: main_file file_date_updated: 2020-07-14T12:47:48Z has_accepted_license: '1' language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: '5' publication_status: draft publisher: IST Austria status: public title: Playful Math - An introduction to mathematical games type: working_paper user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2014' ... --- _id: '2270' abstract: - lang: eng text: "Representation languages for coalitional games are a key research area in algorithmic game theory. There is an inher-\r\nent tradeoff between how general a language is, allowing it to capture more elaborate games, and how hard \ it is computationally to optimize and solve such games. One prominent such \ language is the simple yet expressive\r\nWeighted Graph Games (WGGs) representation (Deng and Papadimitriou 1994), which maintains knowledge about synergies between agents in the form of an edge weighted graph. We consider the problem of finding \ the optimal coalition structure in WGGs. The agents in such games are vertices in a graph, and the value of a coalition is the sum of the weights of the edges present between coalition members. The optimal coalition structure is a partition of the agents to coalitions, that maximizes the sum of utilities obtained by the coalitions. We show that finding the optimal coalition structure is not only hard for general graphs, but is also intractable for restricted families such as planar graphs which are amenable for many other combinatorial problems. \ We then provide algorithms with constant factor approximations for planar, minorfree and bounded degree graphs." author: - first_name: Yoram full_name: Bachrach, Yoram last_name: Bachrach - first_name: Pushmeet full_name: Kohli, Pushmeet last_name: Kohli - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Morteza full_name: Zadimoghaddam, Morteza last_name: Zadimoghaddam citation: ama: 'Bachrach Y, Kohli P, Kolmogorov V, Zadimoghaddam M. Optimal Coalition Structures in Cooperative Graph Games. In: AAAI Press; 2013:81-87.' apa: 'Bachrach, Y., Kohli, P., Kolmogorov, V., & Zadimoghaddam, M. (2013). Optimal Coalition Structures in Cooperative Graph Games (pp. 81–87). Presented at the AAAI: Conference on Artificial Intelligence, Bellevue, WA, United States: AAAI Press.' chicago: Bachrach, Yoram, Pushmeet Kohli, Vladimir Kolmogorov, and Morteza Zadimoghaddam. “Optimal Coalition Structures in Cooperative Graph Games,” 81–87. AAAI Press, 2013. ieee: 'Y. Bachrach, P. Kohli, V. Kolmogorov, and M. Zadimoghaddam, “Optimal Coalition Structures in Cooperative Graph Games,” presented at the AAAI: Conference on Artificial Intelligence, Bellevue, WA, United States, 2013, pp. 81–87.' ista: 'Bachrach Y, Kohli P, Kolmogorov V, Zadimoghaddam M. 2013. Optimal Coalition Structures in Cooperative Graph Games. AAAI: Conference on Artificial Intelligence, 81–87.' mla: Bachrach, Yoram, et al. Optimal Coalition Structures in Cooperative Graph Games. AAAI Press, 2013, pp. 81–87. short: Y. Bachrach, P. Kohli, V. Kolmogorov, M. Zadimoghaddam, in:, AAAI Press, 2013, pp. 81–87. conference: end_date: 2013-07-18 location: Bellevue, WA, United States name: 'AAAI: Conference on Artificial Intelligence' start_date: 2013-07-14 date_created: 2018-12-11T11:56:41Z date_published: 2013-12-31T00:00:00Z date_updated: 2021-01-12T06:56:25Z day: '31' department: - _id: VlKo external_id: arxiv: - '1108.5248' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1108.5248 month: '12' oa: 1 oa_version: None page: 81-87 publication_status: published publisher: AAAI Press publist_id: '4674' quality_controlled: '1' status: public title: Optimal Coalition Structures in Cooperative Graph Games type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2013' ... --- _id: '2274' abstract: - lang: eng text: "Proofs of work (PoW) have been suggested by Dwork and Naor (Crypto'92) as protection to a shared resource. The basic idea is to ask the service requestor to dedicate some non-trivial amount of computational work to every request. The original applications included prevention of spam and protection against denial of service attacks. More recently, PoWs have been used to prevent double spending in the Bitcoin digital currency system.\r\n\r\nIn this work, we put forward an alternative concept for PoWs -- so-called proofs of space (PoS), where a service requestor must dedicate a significant amount of disk space as opposed to computation. We construct secure PoS schemes in the random oracle model, using graphs with high "pebbling complexity" and Merkle hash-trees. " author: - first_name: Stefan full_name: Dziembowski, Stefan last_name: Dziembowski - first_name: Sebastian full_name: Faust, Sebastian last_name: Faust - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Krzysztof Z full_name: Pietrzak, Krzysztof Z id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87 last_name: Pietrzak orcid: 0000-0002-9139-1654 citation: ama: Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. Proofs of Space. IST Austria; 2013. apa: Dziembowski, S., Faust, S., Kolmogorov, V., & Pietrzak, K. Z. (2013). Proofs of Space. IST Austria. chicago: Dziembowski, Stefan, Sebastian Faust, Vladimir Kolmogorov, and Krzysztof Z Pietrzak. Proofs of Space. IST Austria, 2013. ieee: S. Dziembowski, S. Faust, V. Kolmogorov, and K. Z. Pietrzak, Proofs of Space. IST Austria, 2013. ista: Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. 2013. Proofs of Space, IST Austria,p. mla: Dziembowski, Stefan, et al. Proofs of Space. IST Austria, 2013. short: S. Dziembowski, S. Faust, V. Kolmogorov, K.Z. Pietrzak, Proofs of Space, IST Austria, 2013. date_created: 2018-12-11T11:56:42Z date_published: 2013-11-28T00:00:00Z date_updated: 2023-02-23T10:09:33Z day: '28' ddc: - '530' department: - _id: VlKo - _id: KrPi file: - access_level: open_access checksum: 37b61637b62fc079d9141c59d9f1a94f content_type: application/pdf creator: system date_created: 2018-12-12T10:16:11Z date_updated: 2020-07-14T12:45:36Z file_id: '5197' file_name: IST-2016-671-v1+1_796.pdf file_size: 405870 relation: main_file file_date_updated: 2020-07-14T12:45:36Z has_accepted_license: '1' language: - iso: eng month: '11' oa: 1 oa_version: Published Version publication_status: published publisher: IST Austria publist_id: '4670' pubrep_id: '671' related_material: record: - id: '1675' relation: later_version status: public scopus_import: 1 status: public title: Proofs of Space type: report user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2013' ... --- _id: '2273' abstract: - lang: eng text: We propose a new family of message passing techniques for MAP estimation in graphical models which we call Sequential Reweighted Message Passing (SRMP). Special cases include well-known techniques such as Min-Sum Diusion (MSD) and a faster Sequential Tree-Reweighted Message Passing (TRW-S). Importantly, our derivation is simpler than the original derivation of TRW-S, and does not involve a decomposition into trees. This allows easy generalizations. We present such a generalization for the case of higher-order graphical models, and test it on several real-world problems with promising results. author: - first_name: Vladimir full_name: Vladimir Kolmogorov id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Kolmogorov V. Reweighted Message Passing Revisited. IST Austria; 2013. apa: Kolmogorov, V. (2013). Reweighted message passing revisited. IST Austria. chicago: Kolmogorov, Vladimir. Reweighted Message Passing Revisited. IST Austria, 2013. ieee: V. Kolmogorov, Reweighted message passing revisited. IST Austria, 2013. ista: Kolmogorov V. 2013. Reweighted message passing revisited, IST Austria,p. mla: Kolmogorov, Vladimir. Reweighted Message Passing Revisited. IST Austria, 2013. short: V. Kolmogorov, Reweighted Message Passing Revisited, IST Austria, 2013. date_created: 2018-12-11T11:56:42Z date_published: 2013-09-22T00:00:00Z date_updated: 2019-01-24T13:07:32Z day: '22' department: - _id: VlKo extern: 0 main_file_link: - open_access: '1' url: http://arxiv.org/abs/1309.5655 month: '09' oa: 1 publication_status: published publisher: IST Austria publist_id: '4671' quality_controlled: 0 status: public title: Reweighted message passing revisited type: report year: '2013' ... --- _id: '2276' abstract: - lang: eng text: The problem of minimizing the Potts energy function frequently occurs in computer vision applications. One way to tackle this NP-hard problem was proposed by Kovtun [19, 20]. It identifies a part of an optimal solution by running k maxflow computations, where k is the number of labels. The number of “labeled” pixels can be significant in some applications, e.g. 50-93% in our tests for stereo. We show how to reduce the runtime to O (log k) maxflow computations (or one parametric maxflow computation). Furthermore, the output of our algorithm allows to speed-up the subsequent alpha expansion for the unlabeled part, or can be used as it is for time-critical applications. To derive our technique, we generalize the algorithm of Felzenszwalb et al. [7] for Tree Metrics . We also show a connection to k-submodular functions from combinatorial optimization, and discuss k-submodular relaxations for general energy functions. author: - first_name: Igor full_name: Gridchyn, Igor id: 4B60654C-F248-11E8-B48F-1D18A9856A87 last_name: Gridchyn - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Gridchyn I, Kolmogorov V. Potts model, parametric maxflow and k-submodular functions. In: IEEE; 2013:2320-2327. doi:10.1109/ICCV.2013.288' apa: 'Gridchyn, I., & Kolmogorov, V. (2013). Potts model, parametric maxflow and k-submodular functions (pp. 2320–2327). Presented at the ICCV: International Conference on Computer Vision, Sydney, Australia: IEEE. https://doi.org/10.1109/ICCV.2013.288' chicago: Gridchyn, Igor, and Vladimir Kolmogorov. “Potts Model, Parametric Maxflow and k-Submodular Functions,” 2320–27. IEEE, 2013. https://doi.org/10.1109/ICCV.2013.288. ieee: 'I. Gridchyn and V. Kolmogorov, “Potts model, parametric maxflow and k-submodular functions,” presented at the ICCV: International Conference on Computer Vision, Sydney, Australia, 2013, pp. 2320–2327.' ista: 'Gridchyn I, Kolmogorov V. 2013. Potts model, parametric maxflow and k-submodular functions. ICCV: International Conference on Computer Vision, 2320–2327.' mla: Gridchyn, Igor, and Vladimir Kolmogorov. Potts Model, Parametric Maxflow and k-Submodular Functions. IEEE, 2013, pp. 2320–27, doi:10.1109/ICCV.2013.288. short: I. Gridchyn, V. Kolmogorov, in:, IEEE, 2013, pp. 2320–2327. conference: end_date: 2013-12-08 location: Sydney, Australia name: 'ICCV: International Conference on Computer Vision' start_date: 2013-12-01 date_created: 2018-12-11T11:56:43Z date_published: 2013-12-01T00:00:00Z date_updated: 2021-01-12T06:56:28Z day: '01' department: - _id: JoCs - _id: VlKo doi: 10.1109/ICCV.2013.288 external_id: arxiv: - '1310.1771' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1310.1771 month: '12' oa: 1 oa_version: Preprint page: 2320 - 2327 publication_status: published publisher: IEEE publist_id: '4668' quality_controlled: '1' status: public title: Potts model, parametric maxflow and k-submodular functions type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2013' ... --- _id: '2518' abstract: - lang: eng text: A class of valued constraint satisfaction problems (VCSPs) is characterised by a valued constraint language, a fixed set of cost functions on a finite domain. An instance of the problem is specified by a sum of cost functions from the language with the goal to minimise the sum. We study which classes of finite-valued languages can be solved exactly by the basic linear programming relaxation (BLP). Thapper and Živný showed [20] that if BLP solves the language then the language admits a binary commutative fractional polymorphism. We prove that the converse is also true. This leads to a necessary and a sufficient condition which can be checked in polynomial time for a given language. In contrast, the previous necessary and sufficient condition due to [20] involved infinitely many inequalities. More recently, Thapper and Živný [21] showed (using, in particular, a technique introduced in this paper) that core languages that do not satisfy our condition are NP-hard. Taken together, these results imply that a finite-valued language can either be solved using Linear Programming or is NP-hard. alternative_title: - LNCS author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Kolmogorov V. The power of linear programming for finite-valued CSPs: A constructive characterization. In: Vol 7965. Springer; 2013:625-636. doi:10.1007/978-3-642-39206-1_53' apa: 'Kolmogorov, V. (2013). The power of linear programming for finite-valued CSPs: A constructive characterization (Vol. 7965, pp. 625–636). Presented at the ICALP: Automata, Languages and Programming, Riga, Latvia: Springer. https://doi.org/10.1007/978-3-642-39206-1_53' chicago: 'Kolmogorov, Vladimir. “The Power of Linear Programming for Finite-Valued CSPs: A Constructive Characterization,” 7965:625–36. Springer, 2013. https://doi.org/10.1007/978-3-642-39206-1_53.' ieee: 'V. Kolmogorov, “The power of linear programming for finite-valued CSPs: A constructive characterization,” presented at the ICALP: Automata, Languages and Programming, Riga, Latvia, 2013, vol. 7965, no. 1, pp. 625–636.' ista: 'Kolmogorov V. 2013. The power of linear programming for finite-valued CSPs: A constructive characterization. ICALP: Automata, Languages and Programming, LNCS, vol. 7965, 625–636.' mla: 'Kolmogorov, Vladimir. The Power of Linear Programming for Finite-Valued CSPs: A Constructive Characterization. Vol. 7965, no. 1, Springer, 2013, pp. 625–36, doi:10.1007/978-3-642-39206-1_53.' short: V. Kolmogorov, in:, Springer, 2013, pp. 625–636. conference: end_date: 2013-07-12 location: Riga, Latvia name: 'ICALP: Automata, Languages and Programming' start_date: 2013-07-08 date_created: 2018-12-11T11:58:08Z date_published: 2013-07-01T00:00:00Z date_updated: 2023-02-23T10:35:42Z day: '01' department: - _id: VlKo doi: 10.1007/978-3-642-39206-1_53 external_id: arxiv: - '1207.7213' intvolume: ' 7965' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1207.7213 month: '07' oa: 1 oa_version: Preprint page: 625 - 636 publication_status: published publisher: Springer publist_id: '4383' quality_controlled: '1' related_material: record: - id: '2271' relation: later_version status: public scopus_import: 1 status: public title: 'The power of linear programming for finite-valued CSPs: A constructive characterization' type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 7965 year: '2013' ... --- _id: '2828' abstract: - lang: eng text: 'We study the complexity of valued constraint satisfaction problems (VCSPs) parametrized by a constraint language, a fixed set of cost functions over a finite domain. An instance of the problem is specified by a sum of cost functions from the language and the goal is to minimize the sum. Under the unique games conjecture, the approximability of finite-valued VCSPs is well understood, see Raghavendra [2008]. However, there is no characterization of finite-valued VCSPs, let alone general-valued VCSPs, that can be solved exactly in polynomial time, thus giving insights from a combinatorial optimization perspective. We consider the case of languages containing all possible unary cost functions. In the case of languages consisting of only {0, ∞}-valued cost functions (i.e., relations), such languages have been called conservative and studied by Bulatov [2003, 2011] and recently by Barto [2011]. Since we study valued languages, we call a language conservative if it contains all finite-valued unary cost functions. The computational complexity of conservative valued languages has been studied by Cohen et al. [2006] for languages over Boolean domains, by Deineko et al. [2008] for {0, 1}-valued languages (a.k.a Max-CSP), and by Takhanov [2010a] for {0, ∞}-valued languages containing all finite-valued unary cost functions (a.k.a. Min-Cost-Hom). We prove a Schaefer-like dichotomy theorem for conservative valued languages: if all cost functions in the language satisfy a certain condition (specified by a complementary combination of STP and MJN multimor-phisms), then any instance can be solved in polynomial time (via a new algorithm developed in this article), otherwise the language is NP-hard. This is the first complete complexity classification of general-valued constraint languages over non-Boolean domains. It is a common phenomenon that complexity classifications of problems over non-Boolean domains are significantly harder than the Boolean cases. The polynomial-time algorithm we present for the tractable cases is a generalization of the submodular minimization problem and a result of Cohen et al. [2008]. Our results generalize previous results by Takhanov [2010a] and (a subset of results) by Cohen et al. [2006] and Deineko et al. [2008]. Moreover, our results do not rely on any computer-assisted search as in Deineko et al. [2008], and provide a powerful tool for proving hardness of finite-valued and general-valued languages.' article_number: '10' author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Stanislav full_name: Živný, Stanislav last_name: Živný citation: ama: Kolmogorov V, Živný S. The complexity of conservative valued CSPs. Journal of the ACM. 2013;60(2). doi:10.1145/2450142.2450146 apa: Kolmogorov, V., & Živný, S. (2013). The complexity of conservative valued CSPs. Journal of the ACM. ACM. https://doi.org/10.1145/2450142.2450146 chicago: Kolmogorov, Vladimir, and Stanislav Živný. “The Complexity of Conservative Valued CSPs.” Journal of the ACM. ACM, 2013. https://doi.org/10.1145/2450142.2450146. ieee: V. Kolmogorov and S. Živný, “The complexity of conservative valued CSPs,” Journal of the ACM, vol. 60, no. 2. ACM, 2013. ista: Kolmogorov V, Živný S. 2013. The complexity of conservative valued CSPs. Journal of the ACM. 60(2), 10. mla: Kolmogorov, Vladimir, and Stanislav Živný. “The Complexity of Conservative Valued CSPs.” Journal of the ACM, vol. 60, no. 2, 10, ACM, 2013, doi:10.1145/2450142.2450146. short: V. Kolmogorov, S. Živný, Journal of the ACM 60 (2013). date_created: 2018-12-11T11:59:48Z date_published: 2013-04-02T00:00:00Z date_updated: 2021-01-12T07:00:00Z day: '02' department: - _id: VlKo doi: 10.1145/2450142.2450146 external_id: arxiv: - '1110.2809' intvolume: ' 60' issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1110.2809 month: '04' oa: 1 oa_version: Preprint publication: Journal of the ACM publication_status: published publisher: ACM publist_id: '3971' quality_controlled: '1' scopus_import: 1 status: public title: The complexity of conservative valued CSPs type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 60 year: '2013' ... --- _id: '2901' abstract: - lang: eng text: ' We introduce the M-modes problem for graphical models: predicting the M label configurations of highest probability that are at the same time local maxima of the probability landscape. M-modes have multiple possible applications: because they are intrinsically diverse, they provide a principled alternative to non-maximum suppression techniques for structured prediction, they can act as codebook vectors for quantizing the configuration space, or they can form component centers for mixture model approximation. We present two algorithms for solving the M-modes problem. The first algorithm solves the problem in polynomial time when the underlying graphical model is a simple chain. The second algorithm solves the problem for junction chains. In synthetic and real dataset, we demonstrate how M-modes can improve the performance of prediction. We also use the generated modes as a tool to understand the topography of the probability distribution of configurations, for example with relation to the training set size and amount of noise in the data. ' alternative_title: - ' JMLR: W&CP' author: - first_name: Chao full_name: Chen, Chao id: 3E92416E-F248-11E8-B48F-1D18A9856A87 last_name: Chen - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Zhu full_name: Yan, Zhu last_name: Yan - first_name: Dimitris full_name: Metaxas, Dimitris last_name: Metaxas - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Chen C, Kolmogorov V, Yan Z, Metaxas D, Lampert C. Computing the M most probable modes of a graphical model. In: Vol 31. JMLR; 2013:161-169.' apa: 'Chen, C., Kolmogorov, V., Yan, Z., Metaxas, D., & Lampert, C. (2013). Computing the M most probable modes of a graphical model (Vol. 31, pp. 161–169). Presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States: JMLR.' chicago: Chen, Chao, Vladimir Kolmogorov, Zhu Yan, Dimitris Metaxas, and Christoph Lampert. “Computing the M Most Probable Modes of a Graphical Model,” 31:161–69. JMLR, 2013. ieee: 'C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, and C. Lampert, “Computing the M most probable modes of a graphical model,” presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States, 2013, vol. 31, pp. 161–169.' ista: 'Chen C, Kolmogorov V, Yan Z, Metaxas D, Lampert C. 2013. Computing the M most probable modes of a graphical model. AISTATS: Conference on Uncertainty in Artificial Intelligence, JMLR: W&CP, vol. 31, 161–169.' mla: Chen, Chao, et al. Computing the M Most Probable Modes of a Graphical Model. Vol. 31, JMLR, 2013, pp. 161–69. short: C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, C. Lampert, in:, JMLR, 2013, pp. 161–169. conference: end_date: 2013-05-01 location: Scottsdale, AZ, United States name: ' AISTATS: Conference on Uncertainty in Artificial Intelligence' start_date: 2013-04-29 date_created: 2018-12-11T12:00:14Z date_published: 2013-01-01T00:00:00Z date_updated: 2021-01-12T07:00:35Z day: '01' department: - _id: HeEd - _id: VlKo - _id: ChLa intvolume: ' 31' language: - iso: eng main_file_link: - open_access: '1' url: http://jmlr.org/proceedings/papers/v31/chen13a.html month: '01' oa: 1 oa_version: None page: 161 - 169 publication_status: published publisher: JMLR publist_id: '3846' quality_controlled: '1' scopus_import: 1 status: public title: Computing the M most probable modes of a graphical model type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 31 year: '2013' ... --- _id: '2272' abstract: - lang: eng text: "We consider Conditional Random Fields (CRFs) with pattern-based potentials defined on a chain. In this model the energy of a string (labeling) x1...xn is the sum of terms over intervals [i,j] where each term is non-zero only if the substring xi...xj equals a prespecified pattern α. Such CRFs can be naturally applied to many sequence tagging problems.\r\nWe present efficient algorithms for the three standard inference tasks in a CRF, namely computing (i) the partition function, (ii) marginals, and (iii) computing the MAP. Their complexities are respectively O(nL), O(nLℓmax) and O(nLmin{|D|,log(ℓmax+1)}) where L is the combined length of input patterns, ℓmax is the maximum length of a pattern, and D is the input alphabet. This improves on the previous algorithms of (Ye et al., 2009) whose complexities are respectively O(nL|D|), O(n|Γ|L2ℓ2max) and O(nL|D|), where |Γ| is the number of input patterns.\r\nIn addition, we give an efficient algorithm for sampling. Finally, we consider the case of non-positive weights. (Komodakis & Paragios, 2009) gave an O(nL) algorithm for computing the MAP. We present a modification that has the same worst-case complexity but can beat it in the best case. " alternative_title: - JMLR article_processing_charge: No author: - first_name: Rustem full_name: Takhanov, Rustem id: 2CCAC26C-F248-11E8-B48F-1D18A9856A87 last_name: Takhanov - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Takhanov R, Kolmogorov V. Inference algorithms for pattern-based CRFs on sequence data. In: ICML’13 Proceedings of the 30th International Conference on International. Vol 28. ML Research Press; 2013:145-153.' apa: 'Takhanov, R., & Kolmogorov, V. (2013). Inference algorithms for pattern-based CRFs on sequence data. In ICML’13 Proceedings of the 30th International Conference on International (Vol. 28, pp. 145–153). Atlanta, GA, USA: ML Research Press.' chicago: Takhanov, Rustem, and Vladimir Kolmogorov. “Inference Algorithms for Pattern-Based CRFs on Sequence Data.” In ICML’13 Proceedings of the 30th International Conference on International, 28:145–53. ML Research Press, 2013. ieee: R. Takhanov and V. Kolmogorov, “Inference algorithms for pattern-based CRFs on sequence data,” in ICML’13 Proceedings of the 30th International Conference on International, Atlanta, GA, USA, 2013, vol. 28, no. 3, pp. 145–153. ista: 'Takhanov R, Kolmogorov V. 2013. Inference algorithms for pattern-based CRFs on sequence data. ICML’13 Proceedings of the 30th International Conference on International. ICML: International Conference on Machine Learning, JMLR, vol. 28, 145–153.' mla: Takhanov, Rustem, and Vladimir Kolmogorov. “Inference Algorithms for Pattern-Based CRFs on Sequence Data.” ICML’13 Proceedings of the 30th International Conference on International, vol. 28, no. 3, ML Research Press, 2013, pp. 145–53. short: R. Takhanov, V. Kolmogorov, in:, ICML’13 Proceedings of the 30th International Conference on International, ML Research Press, 2013, pp. 145–153. conference: end_date: 2013-06-21 location: Atlanta, GA, USA name: 'ICML: International Conference on Machine Learning' start_date: 2013-06-16 date_created: 2018-12-11T11:56:41Z date_published: 2013-06-01T00:00:00Z date_updated: 2023-10-17T09:51:32Z day: '01' department: - _id: VlKo intvolume: ' 28' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: http://proceedings.mlr.press/v28/takhanov13.pdf?CFID=105472548&CFTOKEN=5c5859b5d97b4439-27B4AC58-BA92-A964-B598CAACEE6CC515 month: '06' oa: 1 oa_version: Submitted Version page: 145 - 153 publication: ICML'13 Proceedings of the 30th International Conference on International publication_status: published publisher: ML Research Press publist_id: '4672' quality_controlled: '1' related_material: record: - id: '1794' relation: later_version status: public scopus_import: '1' status: public title: Inference algorithms for pattern-based CRFs on sequence data type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 28 year: '2013' ... --- _id: '2930' abstract: - lang: eng text: "In this paper we investigate k-submodular functions. This natural family of discrete functions includes submodular and bisubmodular functions as the special cases k = 1 and k = 2 respectively.\r\n\r\nIn particular we generalize the known Min-Max-Theorem for submodular and bisubmodular functions. This theorem asserts that the minimum of the (bi)submodular function can be found by solving a maximization problem over a (bi)submodular polyhedron. We define a k-submodular polyhedron, prove a Min-Max-Theorem for k-submodular functions, and give a greedy algorithm to construct the vertices of the polyhedron.\r\n" acknowledgement: "We would like to thank Andrei Krokhin for encourag- ing our cooperation, for helpful discussions, and for his critical reading of the manuscript.\r\n" alternative_title: - LNCS author: - first_name: Anna full_name: Huber, Anna last_name: Huber - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: 'Huber A, Kolmogorov V. Towards minimizing k-submodular functions. In: Vol 7422. Springer; 2012:451-462. doi:10.1007/978-3-642-32147-4_40' apa: 'Huber, A., & Kolmogorov, V. (2012). Towards minimizing k-submodular functions (Vol. 7422, pp. 451–462). Presented at the ISCO: International Symposium on Combinatorial Optimization, Athens, Greece: Springer. https://doi.org/10.1007/978-3-642-32147-4_40' chicago: Huber, Anna, and Vladimir Kolmogorov. “Towards Minimizing K-Submodular Functions,” 7422:451–62. Springer, 2012. https://doi.org/10.1007/978-3-642-32147-4_40. ieee: 'A. Huber and V. Kolmogorov, “Towards minimizing k-submodular functions,” presented at the ISCO: International Symposium on Combinatorial Optimization, Athens, Greece, 2012, vol. 7422, pp. 451–462.' ista: 'Huber A, Kolmogorov V. 2012. Towards minimizing k-submodular functions. ISCO: International Symposium on Combinatorial Optimization, LNCS, vol. 7422, 451–462.' mla: Huber, Anna, and Vladimir Kolmogorov. Towards Minimizing K-Submodular Functions. Vol. 7422, Springer, 2012, pp. 451–62, doi:10.1007/978-3-642-32147-4_40. short: A. Huber, V. Kolmogorov, in:, Springer, 2012, pp. 451–462. conference: end_date: 2012-04-21 location: Athens, Greece name: 'ISCO: International Symposium on Combinatorial Optimization' start_date: 2012-04-19 date_created: 2018-12-11T12:00:24Z date_published: 2012-04-01T00:00:00Z date_updated: 2021-01-12T07:00:46Z day: '01' department: - _id: VlKo doi: 10.1007/978-3-642-32147-4_40 intvolume: ' 7422' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1309.5469 month: '04' oa: 1 oa_version: Preprint page: 451 - 462 publication_status: published publisher: Springer publist_id: '3806' quality_controlled: '1' scopus_import: 1 status: public title: Towards minimizing k-submodular functions type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 7422 year: '2012' ... --- _id: '2928' abstract: - lang: eng text: ' This paper addresses the problem of approximate MAP-MRF inference in general graphical models. Following [36], we consider a family of linear programming relaxations of the problem where each relaxation is specified by a set of nested pairs of factors for which the marginalization constraint needs to be enforced. We develop a generalization of the TRW-S algorithm [9] for this problem, where we use a decomposition into junction chains, monotonic w.r.t. some ordering on the nodes. This generalizes the monotonic chains in [9] in a natural way. We also show how to deal with nested factors in an efficient way. Experiments show an improvement over min-sum diffusion, MPLP and subgradient ascent algorithms on a number of computer vision and natural language processing problems. ' article_processing_charge: No author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Thomas full_name: Schoenemann, Thomas last_name: Schoenemann citation: ama: Kolmogorov V, Schoenemann T. Generalized sequential tree-reweighted message passing. arXiv. 2012. apa: Kolmogorov, V., & Schoenemann, T. (2012). Generalized sequential tree-reweighted message passing. arXiv. ArXiv. chicago: Kolmogorov, Vladimir, and Thomas Schoenemann. “Generalized Sequential Tree-Reweighted Message Passing.” ArXiv. ArXiv, 2012. ieee: V. Kolmogorov and T. Schoenemann, “Generalized sequential tree-reweighted message passing,” arXiv. ArXiv, 2012. ista: Kolmogorov V, Schoenemann T. 2012. Generalized sequential tree-reweighted message passing. arXiv, . mla: Kolmogorov, Vladimir, and Thomas Schoenemann. “Generalized Sequential Tree-Reweighted Message Passing.” ArXiv, ArXiv, 2012. short: V. Kolmogorov, T. Schoenemann, ArXiv (2012). date_created: 2018-12-11T12:00:23Z date_published: 2012-05-29T00:00:00Z date_updated: 2021-01-12T07:00:45Z day: '29' department: - _id: VlKo external_id: arxiv: - '1205.6352' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1205.6352 month: '05' oa: 1 oa_version: Preprint page: '16' publication: arXiv publication_status: published publisher: ArXiv publist_id: '3809' status: public title: Generalized sequential tree-reweighted message passing type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2012' ... --- _id: '2931' abstract: - lang: eng text: "In this paper, we present a new approach for establishing correspondences between sparse image features related by an unknown nonrigid mapping and corrupted by clutter and occlusion, such as points extracted from images of different instances of the same object category. We formulate this matching task as an energy minimization problem by defining an elaborate objective function of the appearance and the spatial arrangement of the features. Optimization of this energy is an instance of graph matching, which is in general an NP-hard problem. We describe a novel graph matching optimization technique, which we refer to as dual decomposition (DD), and demonstrate on a variety of examples that this method outperforms existing graph matching algorithms. In the majority of our examples, DD is able to find the global minimum within a minute. The ability to globally optimize the objective allows us to accurately learn the parameters of our matching model from training examples. We show on several matching tasks that our learned model yields results superior to those of state-of-the-art methods.\r\n" acknowledgement: This research was funded in part by Microsoft Research. author: - first_name: Lorenzo full_name: Torresani, Lorenzo last_name: Torresani - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Carsten full_name: Rother, Carsten last_name: Rother citation: ama: Torresani L, Kolmogorov V, Rother C. A dual decomposition approach to feature correspondence. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2012;35(2):259-271. doi:10.1109/TPAMI.2012.105 apa: Torresani, L., Kolmogorov, V., & Rother, C. (2012). A dual decomposition approach to feature correspondence. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2012.105 chicago: Torresani, Lorenzo, Vladimir Kolmogorov, and Carsten Rother. “A Dual Decomposition Approach to Feature Correspondence.” IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2012. https://doi.org/10.1109/TPAMI.2012.105. ieee: L. Torresani, V. Kolmogorov, and C. Rother, “A dual decomposition approach to feature correspondence,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 2. IEEE, pp. 259–271, 2012. ista: Torresani L, Kolmogorov V, Rother C. 2012. A dual decomposition approach to feature correspondence. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35(2), 259–271. mla: Torresani, Lorenzo, et al. “A Dual Decomposition Approach to Feature Correspondence.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 2, IEEE, 2012, pp. 259–71, doi:10.1109/TPAMI.2012.105. short: L. Torresani, V. Kolmogorov, C. Rother, IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (2012) 259–271. date_created: 2018-12-11T12:00:24Z date_published: 2012-05-08T00:00:00Z date_updated: 2021-01-12T07:00:46Z day: '08' department: - _id: VlKo doi: 10.1109/TPAMI.2012.105 intvolume: ' 35' issue: '2' language: - iso: eng month: '05' oa_version: None page: 259 - 271 project: - _id: 2587B514-B435-11E9-9278-68D0E5697425 name: Microsoft Research Faculty Fellowship publication: IEEE Transactions on Pattern Analysis and Machine Intelligence publication_status: published publisher: IEEE publist_id: '3805' quality_controlled: '1' scopus_import: 1 status: public title: A dual decomposition approach to feature correspondence type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2012' ... --- _id: '3117' abstract: - lang: eng text: We consider the problem of minimizing a function represented as a sum of submodular terms. We assume each term allows an efficient computation of exchange capacities. This holds, for example, for terms depending on a small number of variables, or for certain cardinality-dependent terms. A naive application of submodular minimization algorithms would not exploit the existence of specialized exchange capacity subroutines for individual terms. To overcome this, we cast the problem as a submodular flow (SF) problem in an auxiliary graph in such a way that applying most existing SF algorithms would rely only on these subroutines. We then explore in more detail Iwata's capacity scaling approach for submodular flows (Iwata 1997 [19]). In particular, we show how to improve its complexity in the case when the function contains cardinality-dependent terms. author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Kolmogorov V. Minimizing a sum of submodular functions. Discrete Applied Mathematics. 2012;160(15):2246-2258. doi:10.1016/j.dam.2012.05.025 apa: Kolmogorov, V. (2012). Minimizing a sum of submodular functions. Discrete Applied Mathematics. Elsevier. https://doi.org/10.1016/j.dam.2012.05.025 chicago: Kolmogorov, Vladimir. “Minimizing a Sum of Submodular Functions.” Discrete Applied Mathematics. Elsevier, 2012. https://doi.org/10.1016/j.dam.2012.05.025. ieee: V. Kolmogorov, “Minimizing a sum of submodular functions,” Discrete Applied Mathematics, vol. 160, no. 15. Elsevier, pp. 2246–2258, 2012. ista: Kolmogorov V. 2012. Minimizing a sum of submodular functions. Discrete Applied Mathematics. 160(15), 2246–2258. mla: Kolmogorov, Vladimir. “Minimizing a Sum of Submodular Functions.” Discrete Applied Mathematics, vol. 160, no. 15, Elsevier, 2012, pp. 2246–58, doi:10.1016/j.dam.2012.05.025. short: V. Kolmogorov, Discrete Applied Mathematics 160 (2012) 2246–2258. date_created: 2018-12-11T12:01:29Z date_published: 2012-10-01T00:00:00Z date_updated: 2021-01-12T07:41:11Z day: '01' department: - _id: VlKo doi: 10.1016/j.dam.2012.05.025 intvolume: ' 160' issue: '15' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1006.1990 month: '10' oa: 1 oa_version: Preprint page: 2246 - 2258 publication: Discrete Applied Mathematics publication_status: published publisher: Elsevier publist_id: '3582' quality_controlled: '1' scopus_import: 1 status: public title: Minimizing a sum of submodular functions type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 160 year: '2012' ... --- _id: '3257' abstract: - lang: eng text: Consider a convex relaxation f̂ of a pseudo-Boolean function f. We say that the relaxation is totally half-integral if f̂(x) is a polyhedral function with half-integral extreme points x, and this property is preserved after adding an arbitrary combination of constraints of the form x i=x j, x i=1-x j, and x i=γ where γ∈{0,1,1/2} is a constant. A well-known example is the roof duality relaxation for quadratic pseudo-Boolean functions f. We argue that total half-integrality is a natural requirement for generalizations of roof duality to arbitrary pseudo-Boolean functions. Our contributions are as follows. First, we provide a complete characterization of totally half-integral relaxations f̂ by establishing a one-to-one correspondence with bisubmodular functions. Second, we give a new characterization of bisubmodular functions. Finally, we show some relationships between general totally half-integral relaxations and relaxations based on the roof duality. On the conceptual level, our results show that bisubmodular functions provide a natural generalization of the roof duality approach to higher-order terms. This can be viewed as a non-submodular analogue of the fact that submodular functions generalize the s-t minimum cut problem with non-negative weights to higher-order terms. author: - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov citation: ama: Kolmogorov V. Generalized roof duality and bisubmodular functions. Discrete Applied Mathematics. 2012;160(4-5):416-426. doi:10.1016/j.dam.2011.10.026 apa: Kolmogorov, V. (2012). Generalized roof duality and bisubmodular functions. Discrete Applied Mathematics. Elsevier. https://doi.org/10.1016/j.dam.2011.10.026 chicago: Kolmogorov, Vladimir. “Generalized Roof Duality and Bisubmodular Functions.” Discrete Applied Mathematics. Elsevier, 2012. https://doi.org/10.1016/j.dam.2011.10.026. ieee: V. Kolmogorov, “Generalized roof duality and bisubmodular functions,” Discrete Applied Mathematics, vol. 160, no. 4–5. Elsevier, pp. 416–426, 2012. ista: Kolmogorov V. 2012. Generalized roof duality and bisubmodular functions. Discrete Applied Mathematics. 160(4–5), 416–426. mla: Kolmogorov, Vladimir. “Generalized Roof Duality and Bisubmodular Functions.” Discrete Applied Mathematics, vol. 160, no. 4–5, Elsevier, 2012, pp. 416–26, doi:10.1016/j.dam.2011.10.026. short: V. Kolmogorov, Discrete Applied Mathematics 160 (2012) 416–426. date_created: 2018-12-11T12:02:18Z date_published: 2012-03-01T00:00:00Z date_updated: 2023-02-23T11:04:49Z day: '01' department: - _id: VlKo doi: 10.1016/j.dam.2011.10.026 external_id: arxiv: - '1005.2305' intvolume: ' 160' issue: 4-5 language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1005.2305 month: '03' oa: 1 oa_version: Preprint page: 416 - 426 publication: Discrete Applied Mathematics publication_status: published publisher: Elsevier publist_id: '3397' quality_controlled: '1' related_material: record: - id: '2934' relation: earlier_version status: public scopus_import: 1 status: public title: Generalized roof duality and bisubmodular functions type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 160 year: '2012' ... --- _id: '3124' abstract: - lang: eng text: "We consider the problem of inference in a graphical model with binary variables. While in theory it is arguably preferable to compute marginal probabilities, in practice researchers often use MAP inference due to the availability of efficient discrete optimization algorithms. We bridge the gap between the two approaches by introducing the Discrete Marginals technique in which approximate marginals are obtained by minimizing an objective function with unary and pairwise terms over a discretized domain. This allows the use of techniques originally developed for MAP-MRF inference and learning. We explore two ways to set up the objective function - by discretizing the Bethe free energy and by learning it from training data. Experimental results show that for certain types of graphs a learned function can outperform the Bethe approximation. We also establish a link between the Bethe free energy and submodular functions.\r\n" alternative_title: - Inferning 2012 author: - first_name: Filip full_name: Korc, Filip id: 476A2FD6-F248-11E8-B48F-1D18A9856A87 last_name: Korc - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Korc F, Kolmogorov V, Lampert C. Approximating marginals using discrete energy minimization. In: ICML; 2012.' apa: 'Korc, F., Kolmogorov, V., & Lampert, C. (2012). Approximating marginals using discrete energy minimization. Presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland: ICML.' chicago: Korc, Filip, Vladimir Kolmogorov, and Christoph Lampert. “Approximating Marginals Using Discrete Energy Minimization.” ICML, 2012. ieee: 'F. Korc, V. Kolmogorov, and C. Lampert, “Approximating marginals using discrete energy minimization,” presented at the ICML: International Conference on Machine Learning, Edinburgh, Scotland, 2012.' ista: 'Korc F, Kolmogorov V, Lampert C. 2012. Approximating marginals using discrete energy minimization. ICML: International Conference on Machine Learning, Inferning 2012, .' mla: Korc, Filip, et al. Approximating Marginals Using Discrete Energy Minimization. ICML, 2012. short: F. Korc, V. Kolmogorov, C. Lampert, in:, ICML, 2012. conference: end_date: 2012-07-01 location: Edinburgh, Scotland name: 'ICML: International Conference on Machine Learning' start_date: 2012-06-26 date_created: 2018-12-11T12:01:31Z date_published: 2012-06-30T00:00:00Z date_updated: 2023-02-23T12:24:24Z day: '30' ddc: - '000' department: - _id: ChLa - _id: VlKo file: - access_level: open_access checksum: 3d0d4246548c736857302aadb2ff5d15 content_type: application/pdf creator: system date_created: 2018-12-12T10:11:34Z date_updated: 2020-07-14T12:46:00Z file_id: '4889' file_name: IST-2016-565-v1+1_DM-inferning2012.pdf file_size: 305836 relation: main_file file_date_updated: 2020-07-14T12:46:00Z has_accepted_license: '1' language: - iso: eng month: '06' oa: 1 oa_version: Submitted Version publication_status: published publisher: ICML publist_id: '3575' pubrep_id: '565' quality_controlled: '1' related_material: record: - id: '5396' relation: later_version status: public status: public title: Approximating marginals using discrete energy minimization type: conference user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 year: '2012' ... --- _id: '5396' abstract: - lang: eng text: We consider the problem of inference in agraphical model with binary variables. While in theory it is arguably preferable to compute marginal probabilities, in practice researchers often use MAP inference due to the availability of efficient discrete optimization algorithms. We bridge the gap between the two approaches by introducing the Discrete Marginals technique in which approximate marginals are obtained by minimizing an objective function with unary and pair-wise terms over a discretized domain. This allows the use of techniques originally devel-oped for MAP-MRF inference and learning. We explore two ways to set up the objective function - by discretizing the Bethe free energy and by learning it from training data. Experimental results show that for certain types of graphs a learned function can out-perform the Bethe approximation. We also establish a link between the Bethe free energy and submodular functions. alternative_title: - IST Austria Technical Report author: - first_name: Filip full_name: Korc, Filip id: 476A2FD6-F248-11E8-B48F-1D18A9856A87 last_name: Korc - first_name: Vladimir full_name: Kolmogorov, Vladimir id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87 last_name: Kolmogorov - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: Korc F, Kolmogorov V, Lampert C. Approximating Marginals Using Discrete Energy Minimization. IST Austria; 2012. doi:10.15479/AT:IST-2012-0003 apa: Korc, F., Kolmogorov, V., & Lampert, C. (2012). Approximating marginals using discrete energy minimization. IST Austria. https://doi.org/10.15479/AT:IST-2012-0003 chicago: Korc, Filip, Vladimir Kolmogorov, and Christoph Lampert. Approximating Marginals Using Discrete Energy Minimization. IST Austria, 2012. https://doi.org/10.15479/AT:IST-2012-0003. ieee: F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012. ista: Korc F, Kolmogorov V, Lampert C. 2012. Approximating marginals using discrete energy minimization, IST Austria, 13p. mla: Korc, Filip, et al. Approximating Marginals Using Discrete Energy Minimization. IST Austria, 2012, doi:10.15479/AT:IST-2012-0003. short: F. Korc, V. Kolmogorov, C. Lampert, Approximating Marginals Using Discrete Energy Minimization, IST Austria, 2012. date_created: 2018-12-12T11:39:06Z date_published: 2012-07-23T00:00:00Z date_updated: 2023-02-23T11:13:22Z day: '23' ddc: - '000' department: - _id: VlKo - _id: ChLa doi: 10.15479/AT:IST-2012-0003 file: - access_level: open_access checksum: 7e0ba85ad123b13223aaf6cdde2d288c content_type: application/pdf creator: system date_created: 2018-12-12T11:53:29Z date_updated: 2020-07-14T12:46:44Z file_id: '5490' file_name: IST-2012-0003_IST-2012-0003.pdf file_size: 618744 relation: main_file file_date_updated: 2020-07-14T12:46:44Z has_accepted_license: '1' language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: '13' publication_identifier: issn: - 2664-1690 publication_status: published publisher: IST Austria pubrep_id: '36' related_material: record: - id: '3124' relation: earlier_version status: public status: public title: Approximating marginals using discrete energy minimization type: technical_report user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2012' ...