---
_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
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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'
...