--- _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" acknowledgement: We thank the anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions. Open access funding provided by Institute of Science and Technology (IST Austria). article_number: '2109.10203' article_processing_charge: Yes (via OA deal) article_type: original 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. Mathematical Programming. 2024. doi:10.1007/s10107-024-02064-5 apa: Dvorak, M., & Kolmogorov, V. (2024). Generalized minimum 0-extension problem and discrete convexity. Mathematical Programming. Springer Nature. https://doi.org/10.1007/s10107-024-02064-5 chicago: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” Mathematical Programming. Springer Nature, 2024. https://doi.org/10.1007/s10107-024-02064-5. ieee: M. Dvorak and V. Kolmogorov, “Generalized minimum 0-extension problem and discrete convexity,” Mathematical Programming. Springer Nature, 2024. ista: Dvorak M, Kolmogorov V. 2024. Generalized minimum 0-extension problem and discrete convexity. Mathematical Programming., 2109.10203. mla: Dvorak, Martin, and Vladimir Kolmogorov. “Generalized Minimum 0-Extension Problem and Discrete Convexity.” Mathematical Programming, 2109.10203, Springer Nature, 2024, doi:10.1007/s10107-024-02064-5. short: M. Dvorak, V. Kolmogorov, Mathematical Programming (2024). date_created: 2021-09-27T10:48:23Z date_published: 2024-03-07T00:00:00Z date_updated: 2024-03-19T08:20:31Z day: '07' ddc: - '004' department: - _id: GradSch - _id: VlKo doi: 10.1007/s10107-024-02064-5 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 license: https://creativecommons.org/licenses/by/4.0/ month: '03' oa: 1 oa_version: Preprint publication: Mathematical Programming publication_identifier: eissn: - 1436-4646 issn: - 0025-5610 publication_status: epub_ahead publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Generalized minimum 0-extension problem and discrete convexity 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: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2024' ... --- _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 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: '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: '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: '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: '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: '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: '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: '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: '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: '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: '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: '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: '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: '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' ...