---
_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
license: https://creativecommons.org/licenses/by/4.0/
month: '07'
oa: 1
oa_version: Published Version
page: 77:1-77:12
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: 46th International Colloquium on Automata, Languages and Programming
publication_identifier:
isbn:
- 978-3-95977-109-2
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: 1
status: public
title: Testing the complexity of a valued CSP language
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 132
year: '2019'
...
---
_id: '6596'
abstract:
- lang: eng
text: It is well known that many problems in image recovery, signal processing,
and machine learning can be modeled as finding zeros of the sum of maximal monotone
and Lipschitz continuous monotone operators. Many papers have studied forward-backward
splitting methods for finding zeros of the sum of two monotone operators in Hilbert
spaces. Most of the proposed splitting methods in the literature have been proposed
for the sum of maximal monotone and inverse-strongly monotone operators in Hilbert
spaces. In this paper, we consider splitting methods for finding zeros of the
sum of maximal monotone operators and Lipschitz continuous monotone operators
in Banach spaces. We obtain weak and strong convergence results for the zeros
of the sum of maximal monotone and Lipschitz continuous monotone operators in
Banach spaces. Many already studied problems in the literature can be considered
as special cases of this paper.
article_number: '138'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Yekini
full_name: Shehu, Yekini
id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87
last_name: Shehu
orcid: 0000-0001-9224-7139
citation:
ama: Shehu Y. Convergence results of forward-backward algorithms for sum of monotone
operators in Banach spaces. Results in Mathematics. 2019;74(4). doi:10.1007/s00025-019-1061-4
apa: Shehu, Y. (2019). Convergence results of forward-backward algorithms for sum
of monotone operators in Banach spaces. Results in Mathematics. Springer.
https://doi.org/10.1007/s00025-019-1061-4
chicago: Shehu, Yekini. “Convergence Results of Forward-Backward Algorithms for
Sum of Monotone Operators in Banach Spaces.” Results in Mathematics. Springer,
2019. https://doi.org/10.1007/s00025-019-1061-4.
ieee: Y. Shehu, “Convergence results of forward-backward algorithms for sum of monotone
operators in Banach spaces,” Results in Mathematics, vol. 74, no. 4. Springer,
2019.
ista: Shehu Y. 2019. Convergence results of forward-backward algorithms for sum
of monotone operators in Banach spaces. Results in Mathematics. 74(4), 138.
mla: Shehu, Yekini. “Convergence Results of Forward-Backward Algorithms for Sum
of Monotone Operators in Banach Spaces.” Results in Mathematics, vol. 74,
no. 4, 138, Springer, 2019, doi:10.1007/s00025-019-1061-4.
short: Y. Shehu, Results in Mathematics 74 (2019).
date_created: 2019-06-29T10:11:30Z
date_published: 2019-12-01T00:00:00Z
date_updated: 2023-08-28T12:26:22Z
day: '01'
ddc:
- '000'
department:
- _id: VlKo
doi: 10.1007/s00025-019-1061-4
ec_funded: 1
external_id:
arxiv:
- '2101.09068'
isi:
- '000473237500002'
file:
- access_level: open_access
checksum: c6d18cb1e16fc0c36a0e0f30b4ebbc2d
content_type: application/pdf
creator: kschuh
date_created: 2019-07-03T15:20:40Z
date_updated: 2020-07-14T12:47:34Z
file_id: '6605'
file_name: Springer_2019_Shehu.pdf
file_size: 466942
relation: main_file
file_date_updated: 2020-07-14T12:47:34Z
has_accepted_license: '1'
intvolume: ' 74'
isi: 1
issue: '4'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
publication: Results in Mathematics
publication_identifier:
eissn:
- 1420-9012
issn:
- 1422-6383
publication_status: published
publisher: Springer
quality_controlled: '1'
scopus_import: '1'
status: public
title: Convergence results of forward-backward algorithms for sum of monotone operators
in Banach spaces
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 74
year: '2019'
...
---
_id: '7000'
abstract:
- lang: eng
text: The main contributions of this paper are the proposition and the convergence
analysis of a class of inertial projection-type algorithm for solving variational
inequality problems in real Hilbert spaces where the underline operator is monotone
and uniformly continuous. We carry out a unified analysis of the proposed method
under very mild assumptions. In particular, weak convergence of the generated
sequence is established and nonasymptotic O(1 / n) rate of convergence is established,
where n denotes the iteration counter. We also present some experimental results
to illustrate the profits gained by introducing the inertial extrapolation steps.
article_number: '161'
article_processing_charge: No
article_type: original
author:
- first_name: Yekini
full_name: Shehu, Yekini
id: 3FC7CB58-F248-11E8-B48F-1D18A9856A87
last_name: Shehu
orcid: 0000-0001-9224-7139
- first_name: Olaniyi S.
full_name: Iyiola, Olaniyi S.
last_name: Iyiola
- first_name: Xiao-Huan
full_name: Li, Xiao-Huan
last_name: Li
- first_name: Qiao-Li
full_name: Dong, Qiao-Li
last_name: Dong
citation:
ama: Shehu Y, Iyiola OS, Li X-H, Dong Q-L. Convergence analysis of projection method
for variational inequalities. Computational and Applied Mathematics. 2019;38(4).
doi:10.1007/s40314-019-0955-9
apa: Shehu, Y., Iyiola, O. S., Li, X.-H., & Dong, Q.-L. (2019). Convergence
analysis of projection method for variational inequalities. Computational and
Applied Mathematics. Springer Nature. https://doi.org/10.1007/s40314-019-0955-9
chicago: Shehu, Yekini, Olaniyi S. Iyiola, Xiao-Huan Li, and Qiao-Li Dong. “Convergence
Analysis of Projection Method for Variational Inequalities.” Computational
and Applied Mathematics. Springer Nature, 2019. https://doi.org/10.1007/s40314-019-0955-9.
ieee: Y. Shehu, O. S. Iyiola, X.-H. Li, and Q.-L. Dong, “Convergence analysis of
projection method for variational inequalities,” Computational and Applied
Mathematics, vol. 38, no. 4. Springer Nature, 2019.
ista: Shehu Y, Iyiola OS, Li X-H, Dong Q-L. 2019. Convergence analysis of projection
method for variational inequalities. Computational and Applied Mathematics. 38(4),
161.
mla: Shehu, Yekini, et al. “Convergence Analysis of Projection Method for Variational
Inequalities.” Computational and Applied Mathematics, vol. 38, no. 4, 161,
Springer Nature, 2019, doi:10.1007/s40314-019-0955-9.
short: Y. Shehu, O.S. Iyiola, X.-H. Li, Q.-L. Dong, Computational and Applied Mathematics
38 (2019).
date_created: 2019-11-12T12:41:44Z
date_published: 2019-12-01T00:00:00Z
date_updated: 2023-08-30T07:20:32Z
day: '01'
ddc:
- '510'
- '515'
- '518'
department:
- _id: VlKo
doi: 10.1007/s40314-019-0955-9
ec_funded: 1
external_id:
arxiv:
- '2101.09081'
isi:
- '000488973100005'
has_accepted_license: '1'
intvolume: ' 38'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/s40314-019-0955-9
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: Computational and Applied Mathematics
publication_identifier:
eissn:
- 1807-0302
issn:
- 2238-3603
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Convergence analysis of projection method for variational inequalities
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 38
year: '2019'
...
---
_id: '7412'
abstract:
- lang: eng
text: We develop a framework for the rigorous analysis of focused stochastic local
search algorithms. These algorithms search a state space by repeatedly selecting
some constraint that is violated in the current state and moving to a random nearby
state that addresses the violation, while (we hope) not introducing many new violations.
An important class of focused local search algorithms with provable performance
guarantees has recently arisen from algorithmizations of the Lovász local lemma
(LLL), a nonconstructive tool for proving the existence of satisfying states by
introducing a background measure on the state space. While powerful, the state
transitions of algorithms in this class must be, in a precise sense, perfectly
compatible with the background measure. In many applications this is a very restrictive
requirement, and one needs to step outside the class. Here we introduce the notion
of measure distortion and develop a framework for analyzing arbitrary focused
stochastic local search algorithms, recovering LLL algorithmizations as the special
case of no distortion. Our framework takes as input an arbitrary algorithm of
such type and an arbitrary probability measure and shows how to use the measure
as a yardstick of algorithmic progress, even for algorithms designed independently
of the measure.
article_processing_charge: No
article_type: original
author:
- first_name: Dimitris
full_name: Achlioptas, Dimitris
last_name: Achlioptas
- first_name: Fotis
full_name: Iliopoulos, Fotis
last_name: Iliopoulos
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: Achlioptas D, Iliopoulos F, Kolmogorov V. A local lemma for focused stochastical
algorithms. SIAM Journal on Computing. 2019;48(5):1583-1602. doi:10.1137/16m109332x
apa: Achlioptas, D., Iliopoulos, F., & Kolmogorov, V. (2019). A local lemma
for focused stochastical algorithms. SIAM Journal on Computing. SIAM. https://doi.org/10.1137/16m109332x
chicago: Achlioptas, Dimitris, Fotis Iliopoulos, and Vladimir Kolmogorov. “A Local
Lemma for Focused Stochastical Algorithms.” SIAM Journal on Computing.
SIAM, 2019. https://doi.org/10.1137/16m109332x.
ieee: D. Achlioptas, F. Iliopoulos, and V. Kolmogorov, “A local lemma for focused
stochastical algorithms,” SIAM Journal on Computing, vol. 48, no. 5. SIAM,
pp. 1583–1602, 2019.
ista: Achlioptas D, Iliopoulos F, Kolmogorov V. 2019. A local lemma for focused
stochastical algorithms. SIAM Journal on Computing. 48(5), 1583–1602.
mla: Achlioptas, Dimitris, et al. “A Local Lemma for Focused Stochastical Algorithms.”
SIAM Journal on Computing, vol. 48, no. 5, SIAM, 2019, pp. 1583–602, doi:10.1137/16m109332x.
short: D. Achlioptas, F. Iliopoulos, V. Kolmogorov, SIAM Journal on Computing 48
(2019) 1583–1602.
date_created: 2020-01-30T09:27:32Z
date_published: 2019-10-31T00:00:00Z
date_updated: 2023-09-06T15:25:29Z
day: '31'
department:
- _id: VlKo
doi: 10.1137/16m109332x
ec_funded: 1
external_id:
arxiv:
- '1809.01537'
isi:
- '000493900200005'
intvolume: ' 48'
isi: 1
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1809.01537
month: '10'
oa: 1
oa_version: Preprint
page: 1583-1602
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: SIAM Journal on Computing
publication_identifier:
eissn:
- 1095-7111
issn:
- 0097-5397
publication_status: published
publisher: SIAM
quality_controlled: '1'
scopus_import: '1'
status: public
title: A local lemma for focused stochastical algorithms
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 48
year: '2019'
...
---
_id: '7468'
abstract:
- lang: eng
text: We present a new proximal bundle method for Maximum-A-Posteriori (MAP) inference
in structured energy minimization problems. The method optimizes a Lagrangean
relaxation of the original energy minimization problem using a multi plane block-coordinate
Frank-Wolfe method that takes advantage of the specific structure of the Lagrangean
decomposition. We show empirically that our method outperforms state-of-the-art
Lagrangean decomposition based algorithms on some challenging Markov Random Field,
multi-label discrete tomography and graph matching problems.
article_number: 11138-11147
article_processing_charge: No
author:
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Swoboda P, Kolmogorov V. Map inference via block-coordinate Frank-Wolfe algorithm.
In: Proceedings of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition. Vol 2019-June. IEEE; 2019. doi:10.1109/CVPR.2019.01140'
apa: 'Swoboda, P., & Kolmogorov, V. (2019). Map inference via block-coordinate
Frank-Wolfe algorithm. In Proceedings of the IEEE Computer Society Conference
on Computer Vision and Pattern Recognition (Vol. 2019–June). Long Beach, CA,
United States: IEEE. https://doi.org/10.1109/CVPR.2019.01140'
chicago: Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate
Frank-Wolfe Algorithm.” In Proceedings of the IEEE Computer Society Conference
on Computer Vision and Pattern Recognition, Vol. 2019–June. IEEE, 2019. https://doi.org/10.1109/CVPR.2019.01140.
ieee: P. Swoboda and V. Kolmogorov, “Map inference via block-coordinate Frank-Wolfe
algorithm,” in Proceedings of the IEEE Computer Society Conference on Computer
Vision and Pattern Recognition, Long Beach, CA, United States, 2019, vol.
2019–June.
ista: 'Swoboda P, Kolmogorov V. 2019. Map inference via block-coordinate Frank-Wolfe
algorithm. Proceedings of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition
vol. 2019–June, 11138–11147.'
mla: Swoboda, Paul, and Vladimir Kolmogorov. “Map Inference via Block-Coordinate
Frank-Wolfe Algorithm.” Proceedings of the IEEE Computer Society Conference
on Computer Vision and Pattern Recognition, vol. 2019–June, 11138–11147, IEEE,
2019, doi:10.1109/CVPR.2019.01140.
short: P. Swoboda, V. Kolmogorov, in:, Proceedings of the IEEE Computer Society
Conference on Computer Vision and Pattern Recognition, IEEE, 2019.
conference:
end_date: 2019-06-20
location: Long Beach, CA, United States
name: 'CVPR: Conference on Computer Vision and Pattern Recognition'
start_date: 2019-06-15
date_created: 2020-02-09T23:00:52Z
date_published: 2019-06-01T00:00:00Z
date_updated: 2023-09-07T14:54:24Z
day: '01'
department:
- _id: VlKo
doi: 10.1109/CVPR.2019.01140
ec_funded: 1
external_id:
arxiv:
- '1806.05049'
isi:
- '000542649304076'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1806.05049
month: '06'
oa: 1
oa_version: Preprint
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: Proceedings of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition
publication_identifier:
isbn:
- '9781728132938'
issn:
- '10636919'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Map inference via block-coordinate Frank-Wolfe algorithm
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2019-June
year: '2019'
...
---
_id: '7639'
abstract:
- lang: eng
text: Deep neural networks (DNNs) have become increasingly important due to their
excellent empirical performance on a wide range of problems. However, regularization
is generally achieved by indirect means, largely due to the complex set of functions
defined by a network and the difficulty in measuring function complexity. There
exists no method in the literature for additive regularization based on a norm
of the function, as is classically considered in statistical learning theory.
In this work, we study the tractability of function norms for deep neural networks
with ReLU activations. We provide, to the best of our knowledge, the first proof
in the literature of the NP-hardness of computing function norms of DNNs of 3
or more layers. We also highlight a fundamental difference between shallow and
deep networks. In the light on these results, we propose a new regularization
strategy based on approximate function norms, and show its efficiency on a segmentation
task with a DNN.
article_number: 748-752
article_processing_charge: No
author:
- first_name: Amal
full_name: Rannen-Triki, Amal
last_name: Rannen-Triki
- first_name: Maxim
full_name: Berman, Maxim
last_name: Berman
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Matthew B.
full_name: Blaschko, Matthew B.
last_name: Blaschko
citation:
ama: 'Rannen-Triki A, Berman M, Kolmogorov V, Blaschko MB. Function norms for neural
networks. In: Proceedings of the 2019 International Conference on Computer
Vision Workshop. IEEE; 2019. doi:10.1109/ICCVW.2019.00097'
apa: 'Rannen-Triki, A., Berman, M., Kolmogorov, V., & Blaschko, M. B. (2019).
Function norms for neural networks. In Proceedings of the 2019 International
Conference on Computer Vision Workshop. Seoul, South Korea: IEEE. https://doi.org/10.1109/ICCVW.2019.00097'
chicago: Rannen-Triki, Amal, Maxim Berman, Vladimir Kolmogorov, and Matthew B. Blaschko.
“Function Norms for Neural Networks.” In Proceedings of the 2019 International
Conference on Computer Vision Workshop. IEEE, 2019. https://doi.org/10.1109/ICCVW.2019.00097.
ieee: A. Rannen-Triki, M. Berman, V. Kolmogorov, and M. B. Blaschko, “Function norms
for neural networks,” in Proceedings of the 2019 International Conference on
Computer Vision Workshop, Seoul, South Korea, 2019.
ista: 'Rannen-Triki A, Berman M, Kolmogorov V, Blaschko MB. 2019. Function norms
for neural networks. Proceedings of the 2019 International Conference on Computer
Vision Workshop. ICCVW: International Conference on Computer Vision Workshop,
748–752.'
mla: Rannen-Triki, Amal, et al. “Function Norms for Neural Networks.” Proceedings
of the 2019 International Conference on Computer Vision Workshop, 748–752,
IEEE, 2019, doi:10.1109/ICCVW.2019.00097.
short: A. Rannen-Triki, M. Berman, V. Kolmogorov, M.B. Blaschko, in:, Proceedings
of the 2019 International Conference on Computer Vision Workshop, IEEE, 2019.
conference:
end_date: 2019-10-28
location: Seoul, South Korea
name: 'ICCVW: International Conference on Computer Vision Workshop'
start_date: 2019-10-27
date_created: 2020-04-05T22:00:50Z
date_published: 2019-10-01T00:00:00Z
date_updated: 2023-09-08T11:19:12Z
day: '01'
department:
- _id: VlKo
doi: 10.1109/ICCVW.2019.00097
external_id:
isi:
- '000554591600090'
isi: 1
language:
- iso: eng
month: '10'
oa_version: None
publication: Proceedings of the 2019 International Conference on Computer Vision Workshop
publication_identifier:
isbn:
- '9781728150239'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Function norms for neural networks
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2019'
...
---
_id: '703'
abstract:
- lang: eng
text: We consider the NP-hard problem of MAP-inference for undirected discrete graphical
models. We propose a polynomial time and practically efficient algorithm for finding
a part of its optimal solution. Specifically, our algorithm marks some labels
of the considered graphical model either as (i) optimal, meaning that they belong
to all optimal solutions of the inference problem; (ii) non-optimal if they provably
do not belong to any solution. With access to an exact solver of a linear programming
relaxation to the MAP-inference problem, our algorithm marks the maximal possible
(in a specified sense) number of labels. We also present a version of the algorithm,
which has access to a suboptimal dual solver only and still can ensure the (non-)optimality
for the marked labels, although the overall number of the marked labels may decrease.
We propose an efficient implementation, which runs in time comparable to a single
run of a suboptimal dual solver. Our method is well-scalable and shows state-of-the-art
results on computational benchmarks from machine learning and computer vision.
author:
- first_name: Alexander
full_name: Shekhovtsov, Alexander
last_name: Shekhovtsov
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Bogdan
full_name: Savchynskyy, Bogdan
last_name: Savchynskyy
citation:
ama: Shekhovtsov A, Swoboda P, Savchynskyy B. Maximum persistency via iterative
relaxed inference with graphical models. IEEE Transactions on Pattern Analysis
and Machine Intelligence. 2018;40(7):1668-1682. doi:10.1109/TPAMI.2017.2730884
apa: Shekhovtsov, A., Swoboda, P., & Savchynskyy, B. (2018). Maximum persistency
via iterative relaxed inference with graphical models. IEEE Transactions on
Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2017.2730884
chicago: Shekhovtsov, Alexander, Paul Swoboda, and Bogdan Savchynskyy. “Maximum
Persistency via Iterative Relaxed Inference with Graphical Models.” IEEE Transactions
on Pattern Analysis and Machine Intelligence. IEEE, 2018. https://doi.org/10.1109/TPAMI.2017.2730884.
ieee: A. Shekhovtsov, P. Swoboda, and B. Savchynskyy, “Maximum persistency via iterative
relaxed inference with graphical models,” IEEE Transactions on Pattern Analysis
and Machine Intelligence, vol. 40, no. 7. IEEE, pp. 1668–1682, 2018.
ista: Shekhovtsov A, Swoboda P, Savchynskyy B. 2018. Maximum persistency via iterative
relaxed inference with graphical models. IEEE Transactions on Pattern Analysis
and Machine Intelligence. 40(7), 1668–1682.
mla: Shekhovtsov, Alexander, et al. “Maximum Persistency via Iterative Relaxed Inference
with Graphical Models.” IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 40, no. 7, IEEE, 2018, pp. 1668–82, doi:10.1109/TPAMI.2017.2730884.
short: A. Shekhovtsov, P. Swoboda, B. Savchynskyy, IEEE Transactions on Pattern
Analysis and Machine Intelligence 40 (2018) 1668–1682.
date_created: 2018-12-11T11:48:01Z
date_published: 2018-07-01T00:00:00Z
date_updated: 2021-01-12T08:11:32Z
day: '01'
department:
- _id: VlKo
doi: 10.1109/TPAMI.2017.2730884
external_id:
arxiv:
- '1508.07902'
intvolume: ' 40'
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1508.07902
month: '07'
oa: 1
oa_version: Preprint
page: 1668-1682
publication: IEEE Transactions on Pattern Analysis and Machine Intelligence
publication_identifier:
issn:
- '01628828'
publication_status: published
publisher: IEEE
publist_id: '6992'
quality_controlled: '1'
scopus_import: 1
status: public
title: Maximum persistency via iterative relaxed inference with graphical models
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 40
year: '2018'
...
---
_id: '10864'
abstract:
- lang: eng
text: We prove that every congruence distributive variety has directed Jónsson terms,
and every congruence modular variety has directed Gumm terms. The directed terms
we construct witness every case of absorption witnessed by the original Jónsson
or Gumm terms. This result is equivalent to a pair of claims about absorption
for admissible preorders in congruence distributive and congruence modular varieties,
respectively. For finite algebras, these absorption theorems have already seen
significant applications, but until now, it was not clear if the theorems hold
for general algebras as well. Our method also yields a novel proof of a result
by P. Lipparini about the existence of a chain of terms (which we call Pixley
terms) in varieties that are at the same time congruence distributive and k-permutable
for some k.
acknowledgement: The second author was supported by National Science Center grant
DEC-2011-/01/B/ST6/01006.
article_processing_charge: No
author:
- first_name: Alexandr
full_name: Kazda, Alexandr
id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87
last_name: Kazda
- first_name: Marcin
full_name: Kozik, Marcin
last_name: Kozik
- first_name: Ralph
full_name: McKenzie, Ralph
last_name: McKenzie
- first_name: Matthew
full_name: Moore, Matthew
last_name: Moore
citation:
ama: 'Kazda A, Kozik M, McKenzie R, Moore M. Absorption and directed Jónsson terms.
In: Czelakowski J, ed. Don Pigozzi on Abstract Algebraic Logic, Universal Algebra,
and Computer Science. Vol 16. OCTR. Cham: Springer Nature; 2018:203-220. doi:10.1007/978-3-319-74772-9_7'
apa: 'Kazda, A., Kozik, M., McKenzie, R., & Moore, M. (2018). Absorption and
directed Jónsson terms. In J. Czelakowski (Ed.), Don Pigozzi on Abstract Algebraic
Logic, Universal Algebra, and Computer Science (Vol. 16, pp. 203–220). Cham:
Springer Nature. https://doi.org/10.1007/978-3-319-74772-9_7'
chicago: 'Kazda, Alexandr, Marcin Kozik, Ralph McKenzie, and Matthew Moore. “Absorption
and Directed Jónsson Terms.” In Don Pigozzi on Abstract Algebraic Logic, Universal
Algebra, and Computer Science, edited by J Czelakowski, 16:203–20. OCTR. Cham:
Springer Nature, 2018. https://doi.org/10.1007/978-3-319-74772-9_7.'
ieee: 'A. Kazda, M. Kozik, R. McKenzie, and M. Moore, “Absorption and directed Jónsson
terms,” in Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and
Computer Science, vol. 16, J. Czelakowski, Ed. Cham: Springer Nature, 2018,
pp. 203–220.'
ista: 'Kazda A, Kozik M, McKenzie R, Moore M. 2018.Absorption and directed Jónsson
terms. In: Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer
Science. vol. 16, 203–220.'
mla: Kazda, Alexandr, et al. “Absorption and Directed Jónsson Terms.” Don Pigozzi
on Abstract Algebraic Logic, Universal Algebra, and Computer Science, edited
by J Czelakowski, vol. 16, Springer Nature, 2018, pp. 203–20, doi:10.1007/978-3-319-74772-9_7.
short: A. Kazda, M. Kozik, R. McKenzie, M. Moore, in:, J. Czelakowski (Ed.), Don
Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer Science,
Springer Nature, Cham, 2018, pp. 203–220.
date_created: 2022-03-18T10:30:32Z
date_published: 2018-03-21T00:00:00Z
date_updated: 2023-09-05T15:37:18Z
day: '21'
department:
- _id: VlKo
doi: 10.1007/978-3-319-74772-9_7
editor:
- first_name: J
full_name: Czelakowski, J
last_name: Czelakowski
external_id:
arxiv:
- '1502.01072'
intvolume: ' 16'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1502.01072
month: '03'
oa: 1
oa_version: Preprint
page: 203-220
place: Cham
publication: Don Pigozzi on Abstract Algebraic Logic, Universal Algebra, and Computer
Science
publication_identifier:
eisbn:
- '9783319747729'
eissn:
- 2211-2766
isbn:
- '9783319747712'
issn:
- 2211-2758
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
series_title: OCTR
status: public
title: Absorption and directed Jónsson terms
type: book_chapter
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 16
year: '2018'
...
---
_id: '273'
abstract:
- lang: eng
text: The accuracy of information retrieval systems is often measured using complex
loss functions such as the average precision (AP) or the normalized discounted
cumulative gain (NDCG). Given a set of positive and negative samples, the parameters
of a retrieval system can be estimated by minimizing these loss functions. However,
the non-differentiability and non-decomposability of these loss functions does
not allow for simple gradient based optimization algorithms. This issue is generally
circumvented by either optimizing a structured hinge-loss upper bound to the loss
function or by using asymptotic methods like the direct-loss minimization framework.
Yet, the high computational complexity of loss-augmented inference, which is necessary
for both the frameworks, prohibits its use in large training data sets. To alleviate
this deficiency, we present a novel quicksort flavored algorithm for a large class
of non-decomposable loss functions. We provide a complete characterization of
the loss functions that are amenable to our algorithm, and show that it includes
both AP and NDCG based loss functions. Furthermore, we prove that no comparison
based algorithm can improve upon the computational complexity of our approach
asymptotically. We demonstrate the effectiveness of our approach in the context
of optimizing the structured hinge loss upper bound of AP and NDCG loss for learning
models for a variety of vision tasks. We show that our approach provides significantly
better results than simpler decomposable loss functions, while requiring a comparable
training time.
article_processing_charge: No
author:
- first_name: Pritish
full_name: Mohapatra, Pritish
last_name: Mohapatra
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
- first_name: C V
full_name: Jawahar, C V
last_name: Jawahar
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: M Pawan
full_name: Kumar, M Pawan
last_name: Kumar
citation:
ama: 'Mohapatra P, Rolinek M, Jawahar CV, Kolmogorov V, Kumar MP. Efficient optimization
for rank-based loss functions. In: 2018 IEEE/CVF Conference on Computer Vision
and Pattern Recognition. IEEE; 2018:3693-3701. doi:10.1109/cvpr.2018.00389'
apa: 'Mohapatra, P., Rolinek, M., Jawahar, C. V., Kolmogorov, V., & Kumar, M.
P. (2018). Efficient optimization for rank-based loss functions. In 2018 IEEE/CVF
Conference on Computer Vision and Pattern Recognition (pp. 3693–3701). Salt
Lake City, UT, USA: IEEE. https://doi.org/10.1109/cvpr.2018.00389'
chicago: Mohapatra, Pritish, Michal Rolinek, C V Jawahar, Vladimir Kolmogorov, and
M Pawan Kumar. “Efficient Optimization for Rank-Based Loss Functions.” In 2018
IEEE/CVF Conference on Computer Vision and Pattern Recognition, 3693–3701.
IEEE, 2018. https://doi.org/10.1109/cvpr.2018.00389.
ieee: P. Mohapatra, M. Rolinek, C. V. Jawahar, V. Kolmogorov, and M. P. Kumar, “Efficient
optimization for rank-based loss functions,” in 2018 IEEE/CVF Conference on
Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 2018, pp.
3693–3701.
ista: 'Mohapatra P, Rolinek M, Jawahar CV, Kolmogorov V, Kumar MP. 2018. Efficient
optimization for rank-based loss functions. 2018 IEEE/CVF Conference on Computer
Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern
Recognition, 3693–3701.'
mla: Mohapatra, Pritish, et al. “Efficient Optimization for Rank-Based Loss Functions.”
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE,
2018, pp. 3693–701, doi:10.1109/cvpr.2018.00389.
short: P. Mohapatra, M. Rolinek, C.V. Jawahar, V. Kolmogorov, M.P. Kumar, in:, 2018
IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018, pp.
3693–3701.
conference:
end_date: 2018-06-22
location: Salt Lake City, UT, USA
name: 'CVPR: Conference on Computer Vision and Pattern Recognition'
start_date: 2018-06-18
date_created: 2018-12-11T11:45:33Z
date_published: 2018-06-28T00:00:00Z
date_updated: 2023-09-11T13:24:43Z
day: '28'
department:
- _id: VlKo
doi: 10.1109/cvpr.2018.00389
ec_funded: 1
external_id:
arxiv:
- '1604.08269'
isi:
- '000457843603087'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1604.08269
month: '06'
oa: 1
oa_version: Preprint
page: 3693-3701
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
publication_identifier:
isbn:
- '9781538664209'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Efficient optimization for rank-based loss functions
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...
---
_id: '193'
abstract:
- lang: eng
text: 'We show attacks on five data-independent memory-hard functions (iMHF) that
were submitted to the password hashing competition (PHC). Informally, an MHF is
a function which cannot be evaluated on dedicated hardware, like ASICs, at significantly
lower hardware and/or energy cost than evaluating a single instance on a standard
single-core architecture. Data-independent means the memory access pattern of
the function is independent of the input; this makes iMHFs harder to construct
than data-dependent ones, but the latter can be attacked by various side-channel
attacks. Following [Alwen-Blocki''16], we capture the evaluation of an iMHF as
a directed acyclic graph (DAG). The cumulative parallel pebbling complexity of
this DAG is a measure for the hardware cost of evaluating the iMHF on an ASIC.
Ideally, one would like the complexity of a DAG underlying an iMHF to be as close
to quadratic in the number of nodes of the graph as possible. Instead, we show
that (the DAGs underlying) the following iMHFs are far from this bound: Rig.v2,
TwoCats and Gambit each having an exponent no more than 1.75. Moreover, we show
that the complexity of the iMHF modes of the PHC finalists Pomelo and Lyra2 have
exponents at most 1.83 and 1.67 respectively. To show this we investigate a combinatorial
property of each underlying DAG (called its depth-robustness. By establishing
upper bounds on this property we are then able to apply the general technique
of [Alwen-Block''16] for analyzing the hardware costs of an iMHF.'
acknowledgement: Leonid Reyzin was supported in part by IST Austria and by US NSF
grants 1012910, 1012798, and 1422965; this research was performed while he was visiting
IST Austria.
article_processing_charge: No
author:
- first_name: Joel F
full_name: Alwen, Joel F
id: 2A8DFA8C-F248-11E8-B48F-1D18A9856A87
last_name: Alwen
- first_name: Peter
full_name: Gazi, Peter
last_name: Gazi
- first_name: Chethan
full_name: Kamath Hosdurg, Chethan
id: 4BD3F30E-F248-11E8-B48F-1D18A9856A87
last_name: Kamath Hosdurg
- first_name: Karen
full_name: Klein, Karen
id: 3E83A2F8-F248-11E8-B48F-1D18A9856A87
last_name: Klein
- first_name: Georg F
full_name: Osang, Georg F
id: 464B40D6-F248-11E8-B48F-1D18A9856A87
last_name: Osang
orcid: 0000-0002-8882-5116
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
- first_name: Lenoid
full_name: Reyzin, Lenoid
last_name: Reyzin
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
- first_name: Michal
full_name: Rybar, Michal
id: 2B3E3DE8-F248-11E8-B48F-1D18A9856A87
last_name: Rybar
citation:
ama: 'Alwen JF, Gazi P, Kamath Hosdurg C, et al. On the memory hardness of data
independent password hashing functions. In: Proceedings of the 2018 on Asia
Conference on Computer and Communication Security. ACM; 2018:51-65. doi:10.1145/3196494.3196534'
apa: 'Alwen, J. F., Gazi, P., Kamath Hosdurg, C., Klein, K., Osang, G. F., Pietrzak,
K. Z., … Rybar, M. (2018). On the memory hardness of data independent password
hashing functions. In Proceedings of the 2018 on Asia Conference on Computer
and Communication Security (pp. 51–65). Incheon, Republic of Korea: ACM. https://doi.org/10.1145/3196494.3196534'
chicago: Alwen, Joel F, Peter Gazi, Chethan Kamath Hosdurg, Karen Klein, Georg F
Osang, Krzysztof Z Pietrzak, Lenoid Reyzin, Michal Rolinek, and Michal Rybar.
“On the Memory Hardness of Data Independent Password Hashing Functions.” In Proceedings
of the 2018 on Asia Conference on Computer and Communication Security, 51–65.
ACM, 2018. https://doi.org/10.1145/3196494.3196534.
ieee: J. F. Alwen et al., “On the memory hardness of data independent password
hashing functions,” in Proceedings of the 2018 on Asia Conference on Computer
and Communication Security, Incheon, Republic of Korea, 2018, pp. 51–65.
ista: 'Alwen JF, Gazi P, Kamath Hosdurg C, Klein K, Osang GF, Pietrzak KZ, Reyzin
L, Rolinek M, Rybar M. 2018. On the memory hardness of data independent password
hashing functions. Proceedings of the 2018 on Asia Conference on Computer and
Communication Security. ASIACCS: Asia Conference on Computer and Communications
Security , 51–65.'
mla: Alwen, Joel F., et al. “On the Memory Hardness of Data Independent Password
Hashing Functions.” Proceedings of the 2018 on Asia Conference on Computer
and Communication Security, ACM, 2018, pp. 51–65, doi:10.1145/3196494.3196534.
short: J.F. Alwen, P. Gazi, C. Kamath Hosdurg, K. Klein, G.F. Osang, K.Z. Pietrzak,
L. Reyzin, M. Rolinek, M. Rybar, in:, Proceedings of the 2018 on Asia Conference
on Computer and Communication Security, ACM, 2018, pp. 51–65.
conference:
end_date: 2018-06-08
location: Incheon, Republic of Korea
name: 'ASIACCS: Asia Conference on Computer and Communications Security '
start_date: 2018-06-04
date_created: 2018-12-11T11:45:07Z
date_published: 2018-06-01T00:00:00Z
date_updated: 2023-09-13T09:13:12Z
day: '01'
department:
- _id: KrPi
- _id: HeEd
- _id: VlKo
doi: 10.1145/3196494.3196534
ec_funded: 1
external_id:
isi:
- '000516620100005'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2016/783
month: '06'
oa: 1
oa_version: Submitted Version
page: 51 - 65
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
- _id: 258AA5B2-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '682815'
name: Teaching Old Crypto New Tricks
publication: Proceedings of the 2018 on Asia Conference on Computer and Communication
Security
publication_status: published
publisher: ACM
publist_id: '7723'
quality_controlled: '1'
scopus_import: '1'
status: public
title: On the memory hardness of data independent password hashing functions
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...
---
_id: '5975'
abstract:
- lang: eng
text: We consider the recent formulation of the algorithmic Lov ́asz Local Lemma [N.
Har-vey and J. Vondr ́ak, inProceedings of FOCS, 2015, pp. 1327–1345; D. Achlioptas
and F. Iliopoulos,inProceedings of SODA, 2016, pp. 2024–2038; D. Achlioptas, F.
Iliopoulos, and V. Kolmogorov,ALocal Lemma for Focused Stochastic Algorithms,
arXiv preprint, 2018] for finding objects that avoid“bad features,” or “flaws.” It extends the Moser–Tardos resampling algorithm [R. A. Moser andG.
Tardos,J. ACM, 57 (2010), 11] to more general discrete spaces. At each step the
method picks aflaw present in the current state and goes to a new state according
to some prespecified probabilitydistribution (which depends on the current state
and the selected flaw). However, the recent formu-lation is less flexible than
the Moser–Tardos method since it requires a specific flaw selection rule,whereas
the algorithm of Moser and Tardos allows an arbitrary rule (and thus can potentially
beimplemented more efficiently). We formulate a new “commutativity” condition
and prove that it issufficient for an arbitrary rule to work. It also enables
an efficient parallelization under an additionalassumption. We then show that
existing resampling oracles for perfect matchings and permutationsdo satisfy this
condition.
article_processing_charge: No
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: Kolmogorov V. Commutativity in the algorithmic Lovász local lemma. SIAM
Journal on Computing. 2018;47(6):2029-2056. doi:10.1137/16m1093306
apa: Kolmogorov, V. (2018). Commutativity in the algorithmic Lovász local lemma.
SIAM Journal on Computing. Society for Industrial & Applied Mathematics
(SIAM). https://doi.org/10.1137/16m1093306
chicago: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovász Local Lemma.”
SIAM Journal on Computing. Society for Industrial & Applied Mathematics
(SIAM), 2018. https://doi.org/10.1137/16m1093306.
ieee: V. Kolmogorov, “Commutativity in the algorithmic Lovász local lemma,” SIAM
Journal on Computing, vol. 47, no. 6. Society for Industrial & Applied
Mathematics (SIAM), pp. 2029–2056, 2018.
ista: Kolmogorov V. 2018. Commutativity in the algorithmic Lovász local lemma. SIAM
Journal on Computing. 47(6), 2029–2056.
mla: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovász Local Lemma.”
SIAM Journal on Computing, vol. 47, no. 6, Society for Industrial &
Applied Mathematics (SIAM), 2018, pp. 2029–56, doi:10.1137/16m1093306.
short: V. Kolmogorov, SIAM Journal on Computing 47 (2018) 2029–2056.
date_created: 2019-02-13T12:59:33Z
date_published: 2018-11-08T00:00:00Z
date_updated: 2023-09-19T14:24:58Z
day: '08'
department:
- _id: VlKo
doi: 10.1137/16m1093306
ec_funded: 1
external_id:
arxiv:
- '1506.08547'
isi:
- '000453785100001'
intvolume: ' 47'
isi: 1
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1506.08547
month: '11'
oa: 1
oa_version: Preprint
page: 2029-2056
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: SIAM Journal on Computing
publication_identifier:
eissn:
- 1095-7111
issn:
- 0097-5397
publication_status: published
publisher: Society for Industrial & Applied Mathematics (SIAM)
quality_controlled: '1'
related_material:
record:
- id: '1193'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Commutativity in the algorithmic Lovász local lemma
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 47
year: '2018'
...
---
_id: '5978'
abstract:
- lang: eng
text: 'We consider the MAP-inference problem for graphical models,which is a valued
constraint satisfaction problem defined onreal numbers with a natural summation
operation. We proposea family of relaxations (different from the famous Sherali-Adams
hierarchy), which naturally define lower bounds for itsoptimum. This family always
contains a tight relaxation andwe give an algorithm able to find it and therefore,
solve theinitial non-relaxed NP-hard problem.The relaxations we consider decompose
the original probleminto two non-overlapping parts: an easy LP-tight part and
adifficult one. For the latter part a combinatorial solver must beused. As we
show in our experiments, in a number of applica-tions the second, difficult part
constitutes only a small fractionof the whole problem. This property allows to
significantlyreduce the computational time of the combinatorial solver andtherefore
solve problems which were out of reach before.'
article_processing_charge: No
author:
- first_name: Stefan
full_name: Haller, Stefan
last_name: Haller
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Bogdan
full_name: Savchynskyy, Bogdan
last_name: Savchynskyy
citation:
ama: 'Haller S, Swoboda P, Savchynskyy B. Exact MAP-inference by confining combinatorial
search with LP relaxation. In: Proceedings of the 32st AAAI Conference on Artificial
Intelligence. AAAI Press; 2018:6581-6588.'
apa: 'Haller, S., Swoboda, P., & Savchynskyy, B. (2018). Exact MAP-inference
by confining combinatorial search with LP relaxation. In Proceedings of the
32st AAAI Conference on Artificial Intelligence (pp. 6581–6588). New Orleans,
LU, United States: AAAI Press.'
chicago: Haller, Stefan, Paul Swoboda, and Bogdan Savchynskyy. “Exact MAP-Inference
by Confining Combinatorial Search with LP Relaxation.” In Proceedings of the
32st AAAI Conference on Artificial Intelligence, 6581–88. AAAI Press, 2018.
ieee: S. Haller, P. Swoboda, and B. Savchynskyy, “Exact MAP-inference by confining
combinatorial search with LP relaxation,” in Proceedings of the 32st AAAI Conference
on Artificial Intelligence, New Orleans, LU, United States, 2018, pp. 6581–6588.
ista: 'Haller S, Swoboda P, Savchynskyy B. 2018. Exact MAP-inference by confining
combinatorial search with LP relaxation. Proceedings of the 32st AAAI Conference
on Artificial Intelligence. AAAI: Conference on Artificial Intelligence, 6581–6588.'
mla: Haller, Stefan, et al. “Exact MAP-Inference by Confining Combinatorial Search
with LP Relaxation.” Proceedings of the 32st AAAI Conference on Artificial
Intelligence, AAAI Press, 2018, pp. 6581–88.
short: S. Haller, P. Swoboda, B. Savchynskyy, in:, Proceedings of the 32st AAAI
Conference on Artificial Intelligence, AAAI Press, 2018, pp. 6581–6588.
conference:
end_date: 2018-02-07
location: New Orleans, LU, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2018-02-02
date_created: 2019-02-13T13:32:48Z
date_published: 2018-02-01T00:00:00Z
date_updated: 2023-09-19T14:26:52Z
day: '01'
department:
- _id: VlKo
external_id:
arxiv:
- '2004.06370'
isi:
- '000485488906082'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2004.06370
month: '02'
oa: 1
oa_version: Preprint
page: 6581-6588
publication: Proceedings of the 32st AAAI Conference on Artificial Intelligence
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Exact MAP-inference by confining combinatorial search with LP relaxation
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...
---
_id: '18'
abstract:
- lang: eng
text: An N-superconcentrator is a directed, acyclic graph with N input nodes and
N output nodes such that every subset of the inputs and every subset of the outputs
of same cardinality can be connected by node-disjoint paths. It is known that
linear-size and bounded-degree superconcentrators exist. We prove the existence
of such superconcentrators with asymptotic density 25.3 (where the density is
the number of edges divided by N). The previously best known densities were 28
[12] and 27.4136 [17].
article_processing_charge: No
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: Kolmogorov V, Rolinek M. Superconcentrators of density 25.3. Ars Combinatoria.
2018;141(10):269-304.
apa: Kolmogorov, V., & Rolinek, M. (2018). Superconcentrators of density 25.3.
Ars Combinatoria. Charles Babbage Research Centre.
chicago: Kolmogorov, Vladimir, and Michal Rolinek. “Superconcentrators of Density
25.3.” Ars Combinatoria. Charles Babbage Research Centre, 2018.
ieee: V. Kolmogorov and M. Rolinek, “Superconcentrators of density 25.3,” Ars
Combinatoria, vol. 141, no. 10. Charles Babbage Research Centre, pp. 269–304,
2018.
ista: Kolmogorov V, Rolinek M. 2018. Superconcentrators of density 25.3. Ars Combinatoria.
141(10), 269–304.
mla: Kolmogorov, Vladimir, and Michal Rolinek. “Superconcentrators of Density 25.3.”
Ars Combinatoria, vol. 141, no. 10, Charles Babbage Research Centre, 2018,
pp. 269–304.
short: V. Kolmogorov, M. Rolinek, Ars Combinatoria 141 (2018) 269–304.
date_created: 2018-12-11T11:44:11Z
date_published: 2018-10-01T00:00:00Z
date_updated: 2023-09-19T14:46:18Z
day: '01'
department:
- _id: VlKo
external_id:
arxiv:
- '1405.7828'
isi:
- '000446809500022'
intvolume: ' 141'
isi: 1
issue: '10'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1405.7828
month: '10'
oa: 1
oa_version: Preprint
page: 269 - 304
publication: Ars Combinatoria
publication_identifier:
issn:
- 0381-7032
publication_status: published
publisher: Charles Babbage Research Centre
publist_id: '8037'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Superconcentrators of density 25.3
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 141
year: '2018'
...
---
_id: '6032'
abstract:
- lang: eng
text: The main result of this article is a generalization of the classical blossom
algorithm for finding perfect matchings. Our algorithm can efficiently solve Boolean
CSPs where each variable appears in exactly two constraints (we call it edge CSP)
and all constraints are even Δ-matroid relations (represented by lists of tuples).
As a consequence of this, we settle the complexity classification of planar Boolean
CSPs started by Dvorak and Kupec. Using a reduction to even Δ-matroids, we then
extend the tractability result to larger classes of Δ-matroids that we call efficiently
coverable. It properly includes classes that were known to be tractable before,
namely, co-independent, compact, local, linear, and binary, with the following
caveat:We represent Δ-matroids by lists of tuples, while the last two use a representation
by matrices. Since an n ×n matrix can represent exponentially many tuples, our
tractability result is not strictly stronger than the known algorithm for linear
and binary Δ-matroids.
article_number: '22'
article_processing_charge: No
article_type: original
author:
- first_name: Alexandr
full_name: Kazda, Alexandr
id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87
last_name: Kazda
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: Kazda A, Kolmogorov V, Rolinek M. Even delta-matroids and the complexity of
planar boolean CSPs. ACM Transactions on Algorithms. 2018;15(2). doi:10.1145/3230649
apa: Kazda, A., Kolmogorov, V., & Rolinek, M. (2018). Even delta-matroids and
the complexity of planar boolean CSPs. ACM Transactions on Algorithms.
ACM. https://doi.org/10.1145/3230649
chicago: Kazda, Alexandr, Vladimir Kolmogorov, and Michal Rolinek. “Even Delta-Matroids
and the Complexity of Planar Boolean CSPs.” ACM Transactions on Algorithms.
ACM, 2018. https://doi.org/10.1145/3230649.
ieee: A. Kazda, V. Kolmogorov, and M. Rolinek, “Even delta-matroids and the complexity
of planar boolean CSPs,” ACM Transactions on Algorithms, vol. 15, no. 2.
ACM, 2018.
ista: Kazda A, Kolmogorov V, Rolinek M. 2018. Even delta-matroids and the complexity
of planar boolean CSPs. ACM Transactions on Algorithms. 15(2), 22.
mla: Kazda, Alexandr, et al. “Even Delta-Matroids and the Complexity of Planar Boolean
CSPs.” ACM Transactions on Algorithms, vol. 15, no. 2, 22, ACM, 2018, doi:10.1145/3230649.
short: A. Kazda, V. Kolmogorov, M. Rolinek, ACM Transactions on Algorithms 15 (2018).
date_created: 2019-02-17T22:59:25Z
date_published: 2018-12-01T00:00:00Z
date_updated: 2023-09-20T11:20:26Z
day: '01'
department:
- _id: VlKo
doi: 10.1145/3230649
ec_funded: 1
external_id:
arxiv:
- '1602.03124'
isi:
- '000468036500007'
intvolume: ' 15'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1602.03124
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: ACM Transactions on Algorithms
publication_status: published
publisher: ACM
quality_controlled: '1'
related_material:
record:
- id: '1192'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Even delta-matroids and the complexity of planar boolean CSPs
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 15
year: '2018'
...
---
_id: '5573'
abstract:
- lang: eng
text: Graph matching problems for large displacement optical flow of RGB-D images.
article_processing_charge: No
author:
- first_name: Hassan
full_name: Alhaija, Hassan
last_name: Alhaija
- first_name: Anita
full_name: Sellent, Anita
last_name: Sellent
- first_name: Daniel
full_name: Kondermann, Daniel
last_name: Kondermann
- first_name: Carsten
full_name: Rother, Carsten
last_name: Rother
citation:
ama: Alhaija H, Sellent A, Kondermann D, Rother C. Graph matching problems for GraphFlow
– 6D Large Displacement Scene Flow. 2018. doi:10.15479/AT:ISTA:82
apa: Alhaija, H., Sellent, A., Kondermann, D., & Rother, C. (2018). Graph matching
problems for GraphFlow – 6D Large Displacement Scene Flow. Institute of Science
and Technology Austria. https://doi.org/10.15479/AT:ISTA:82
chicago: Alhaija, Hassan, Anita Sellent, Daniel Kondermann, and Carsten Rother.
“Graph Matching Problems for GraphFlow – 6D Large Displacement Scene Flow.” Institute
of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:82.
ieee: H. Alhaija, A. Sellent, D. Kondermann, and C. Rother, “Graph matching problems
for GraphFlow – 6D Large Displacement Scene Flow.” Institute of Science and Technology
Austria, 2018.
ista: Alhaija H, Sellent A, Kondermann D, Rother C. 2018. Graph matching problems
for GraphFlow – 6D Large Displacement Scene Flow, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:82.
mla: Alhaija, Hassan, et al. Graph Matching Problems for GraphFlow – 6D Large
Displacement Scene Flow. Institute of Science and Technology Austria, 2018,
doi:10.15479/AT:ISTA:82.
short: H. Alhaija, A. Sellent, D. Kondermann, C. Rother, (2018).
contributor:
- contributor_type: researcher
first_name: Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
datarep_id: '82'
date_created: 2018-12-12T12:31:36Z
date_published: 2018-01-04T00:00:00Z
date_updated: 2024-02-21T13:41:17Z
day: '04'
ddc:
- '001'
department:
- _id: VlKo
doi: 10.15479/AT:ISTA:82
file:
- access_level: open_access
checksum: 53c17082848e12f3c2e1b4185b578208
content_type: application/zip
creator: system
date_created: 2018-12-12T13:02:34Z
date_updated: 2020-07-14T12:47:05Z
file_id: '5600'
file_name: IST-2018-82-v1+1_GraphFlowMatchingProblems.zip
file_size: 1737958
relation: main_file
file_date_updated: 2020-07-14T12:47:05Z
has_accepted_license: '1'
keyword:
- graph matching
- quadratic assignment problem<
license: https://creativecommons.org/publicdomain/zero/1.0/
month: '01'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
link:
- relation: research_paper
url: https://doi.org/10.1007/978-3-319-24947-6_23
status: public
title: Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '641'
abstract:
- lang: eng
text: 'We introduce two novel methods for learning parameters of graphical models
for image labelling. The following two tasks underline both methods: (i) perturb
model parameters based on given features and ground truth labelings, so as to
exactly reproduce these labelings as optima of the local polytope relaxation of
the labelling problem; (ii) train a predictor for the perturbed model parameters
so that improved model parameters can be applied to the labelling of novel data.
Our first method implements task (i) by inverse linear programming and task (ii)
using a regressor e.g. a Gaussian process. Our second approach simultaneously
solves tasks (i) and (ii) in a joint manner, while being restricted to linearly
parameterised predictors. Experiments demonstrate the merits of both approaches.'
alternative_title:
- LNCS
author:
- first_name: Vera
full_name: Trajkovska, Vera
last_name: Trajkovska
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Freddie
full_name: Åström, Freddie
last_name: Åström
- first_name: Stefanie
full_name: Petra, Stefanie
last_name: Petra
citation:
ama: 'Trajkovska V, Swoboda P, Åström F, Petra S. Graphical model parameter learning
by inverse linear programming. In: Lauze F, Dong Y, Bjorholm Dahl A, eds. Vol
10302. Springer; 2017:323-334. doi:10.1007/978-3-319-58771-4_26'
apa: 'Trajkovska, V., Swoboda, P., Åström, F., & Petra, S. (2017). Graphical
model parameter learning by inverse linear programming. In F. Lauze, Y. Dong,
& A. Bjorholm Dahl (Eds.) (Vol. 10302, pp. 323–334). Presented at the SSVM:
Scale Space and Variational Methods in Computer Vision, Kolding, Denmark: Springer.
https://doi.org/10.1007/978-3-319-58771-4_26'
chicago: Trajkovska, Vera, Paul Swoboda, Freddie Åström, and Stefanie Petra. “Graphical
Model Parameter Learning by Inverse Linear Programming.” edited by François Lauze,
Yiqiu Dong, and Anders Bjorholm Dahl, 10302:323–34. Springer, 2017. https://doi.org/10.1007/978-3-319-58771-4_26.
ieee: 'V. Trajkovska, P. Swoboda, F. Åström, and S. Petra, “Graphical model parameter
learning by inverse linear programming,” presented at the SSVM: Scale Space and
Variational Methods in Computer Vision, Kolding, Denmark, 2017, vol. 10302, pp.
323–334.'
ista: 'Trajkovska V, Swoboda P, Åström F, Petra S. 2017. Graphical model parameter
learning by inverse linear programming. SSVM: Scale Space and Variational Methods
in Computer Vision, LNCS, vol. 10302, 323–334.'
mla: Trajkovska, Vera, et al. Graphical Model Parameter Learning by Inverse Linear
Programming. Edited by François Lauze et al., vol. 10302, Springer, 2017,
pp. 323–34, doi:10.1007/978-3-319-58771-4_26.
short: V. Trajkovska, P. Swoboda, F. Åström, S. Petra, in:, F. Lauze, Y. Dong, A.
Bjorholm Dahl (Eds.), Springer, 2017, pp. 323–334.
conference:
end_date: 2017-06-08
location: Kolding, Denmark
name: 'SSVM: Scale Space and Variational Methods in Computer Vision'
start_date: 2017-06-04
date_created: 2018-12-11T11:47:39Z
date_published: 2017-01-01T00:00:00Z
date_updated: 2021-01-12T08:07:23Z
day: '01'
department:
- _id: VlKo
doi: 10.1007/978-3-319-58771-4_26
editor:
- first_name: François
full_name: Lauze, François
last_name: Lauze
- first_name: Yiqiu
full_name: Dong, Yiqiu
last_name: Dong
- first_name: Anders
full_name: Bjorholm Dahl, Anders
last_name: Bjorholm Dahl
intvolume: ' 10302'
language:
- iso: eng
month: '01'
oa_version: None
page: 323 - 334
publication_identifier:
isbn:
- 978-331958770-7
publication_status: published
publisher: Springer
publist_id: '7147'
quality_controlled: '1'
scopus_import: 1
status: public
title: Graphical model parameter learning by inverse linear programming
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 10302
year: '2017'
...
---
_id: '644'
abstract:
- lang: eng
text: An instance of the valued constraint satisfaction problem (VCSP) is given
by a finite set of variables, a finite domain of labels, and a sum of functions,
each function depending on a subset of the variables. Each function can take finite
values specifying costs of assignments of labels to its variables or the infinite
value, which indicates an infeasible assignment. The goal is to find an assignment
of labels to the variables that minimizes the sum. We study, assuming that P 6=
NP, how the complexity of this very general problem depends on the set of functions
allowed in the instances, the so-called constraint language. The case when all
allowed functions take values in f0;1g corresponds to ordinary CSPs, where one
deals only with the feasibility issue, and there is no optimization. This case
is the subject of the algebraic CSP dichotomy conjecture predicting for which
constraint languages CSPs are tractable (i.e., solvable in polynomial time) and
for which they are NP-hard. The case when all allowed functions take only finite
values corresponds to a finitevalued CSP, where the feasibility aspect is trivial
and one deals only with the optimization issue. The complexity of finite-valued
CSPs was fully classified by Thapper and Živný. An algebraic necessary condition
for tractability of a general-valued CSP with a fixed constraint language was
recently given by Kozik and Ochremiak. As our main result, we prove that if a
constraint language satisfies this algebraic necessary condition, and the feasibility
CSP (i.e., the problem of deciding whether a given instance has a feasible solution)
corresponding to the VCSP with this language is tractable, then the VCSP is tractable.
The algorithm is a simple combination of the assumed algorithm for the feasibility
CSP and the standard LP relaxation. As a corollary, we obtain that a dichotomy
for ordinary CSPs would imply a dichotomy for general-valued CSPs.
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Andrei
full_name: Krokhin, Andrei
last_name: Krokhin
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: Kolmogorov V, Krokhin A, Rolinek M. The complexity of general-valued CSPs.
SIAM Journal on Computing. 2017;46(3):1087-1110. doi:10.1137/16M1091836
apa: Kolmogorov, V., Krokhin, A., & Rolinek, M. (2017). The complexity of general-valued
CSPs. SIAM Journal on Computing. SIAM. https://doi.org/10.1137/16M1091836
chicago: Kolmogorov, Vladimir, Andrei Krokhin, and Michal Rolinek. “The Complexity
of General-Valued CSPs.” SIAM Journal on Computing. SIAM, 2017. https://doi.org/10.1137/16M1091836.
ieee: V. Kolmogorov, A. Krokhin, and M. Rolinek, “The complexity of general-valued
CSPs,” SIAM Journal on Computing, vol. 46, no. 3. SIAM, pp. 1087–1110,
2017.
ista: Kolmogorov V, Krokhin A, Rolinek M. 2017. The complexity of general-valued
CSPs. SIAM Journal on Computing. 46(3), 1087–1110.
mla: Kolmogorov, Vladimir, et al. “The Complexity of General-Valued CSPs.” SIAM
Journal on Computing, vol. 46, no. 3, SIAM, 2017, pp. 1087–110, doi:10.1137/16M1091836.
short: V. Kolmogorov, A. Krokhin, M. Rolinek, SIAM Journal on Computing 46 (2017)
1087–1110.
date_created: 2018-12-11T11:47:40Z
date_published: 2017-06-29T00:00:00Z
date_updated: 2023-02-23T10:07:49Z
day: '29'
department:
- _id: VlKo
doi: 10.1137/16M1091836
ec_funded: 1
intvolume: ' 46'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1502.07327
month: '06'
oa: 1
oa_version: Preprint
page: 1087 - 1110
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: SIAM Journal on Computing
publication_status: published
publisher: SIAM
publist_id: '7138'
quality_controlled: '1'
related_material:
record:
- id: '1637'
relation: other
status: public
scopus_import: 1
status: public
title: The complexity of general-valued CSPs
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 46
year: '2017'
...
---
_id: '646'
abstract:
- lang: eng
text: We present a novel convex relaxation and a corresponding inference algorithm
for the non-binary discrete tomography problem, that is, reconstructing discrete-valued
images from few linear measurements. In contrast to state of the art approaches
that split the problem into a continuous reconstruction problem for the linear
measurement constraints and a discrete labeling problem to enforce discrete-valued
reconstructions, we propose a joint formulation that addresses both problems simultaneously,
resulting in a tighter convex relaxation. For this purpose a constrained graphical
model is set up and evaluated using a novel relaxation optimized by dual decomposition.
We evaluate our approach experimentally and show superior solutions both mathematically
(tighter relaxation) and experimentally in comparison to previously proposed relaxations.
alternative_title:
- LNCS
author:
- first_name: Jan
full_name: Kuske, Jan
last_name: Kuske
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Stefanie
full_name: Petra, Stefanie
last_name: Petra
citation:
ama: 'Kuske J, Swoboda P, Petra S. A novel convex relaxation for non binary discrete
tomography. In: Lauze F, Dong Y, Bjorholm Dahl A, eds. Vol 10302. Springer; 2017:235-246.
doi:10.1007/978-3-319-58771-4_19'
apa: 'Kuske, J., Swoboda, P., & Petra, S. (2017). A novel convex relaxation
for non binary discrete tomography. In F. Lauze, Y. Dong, & A. Bjorholm Dahl
(Eds.) (Vol. 10302, pp. 235–246). Presented at the SSVM: Scale Space and Variational
Methods in Computer Vision, Kolding, Denmark: Springer. https://doi.org/10.1007/978-3-319-58771-4_19'
chicago: Kuske, Jan, Paul Swoboda, and Stefanie Petra. “A Novel Convex Relaxation
for Non Binary Discrete Tomography.” edited by François Lauze, Yiqiu Dong, and
Anders Bjorholm Dahl, 10302:235–46. Springer, 2017. https://doi.org/10.1007/978-3-319-58771-4_19.
ieee: 'J. Kuske, P. Swoboda, and S. Petra, “A novel convex relaxation for non binary
discrete tomography,” presented at the SSVM: Scale Space and Variational Methods
in Computer Vision, Kolding, Denmark, 2017, vol. 10302, pp. 235–246.'
ista: 'Kuske J, Swoboda P, Petra S. 2017. A novel convex relaxation for non binary
discrete tomography. SSVM: Scale Space and Variational Methods in Computer Vision,
LNCS, vol. 10302, 235–246.'
mla: Kuske, Jan, et al. A Novel Convex Relaxation for Non Binary Discrete Tomography.
Edited by François Lauze et al., vol. 10302, Springer, 2017, pp. 235–46, doi:10.1007/978-3-319-58771-4_19.
short: J. Kuske, P. Swoboda, S. Petra, in:, F. Lauze, Y. Dong, A. Bjorholm Dahl
(Eds.), Springer, 2017, pp. 235–246.
conference:
end_date: 2017-06-08
location: Kolding, Denmark
name: 'SSVM: Scale Space and Variational Methods in Computer Vision'
start_date: 2017-06-04
date_created: 2018-12-11T11:47:41Z
date_published: 2017-06-01T00:00:00Z
date_updated: 2021-01-12T08:07:34Z
day: '01'
department:
- _id: VlKo
doi: 10.1007/978-3-319-58771-4_19
ec_funded: 1
editor:
- first_name: François
full_name: Lauze, François
last_name: Lauze
- first_name: Yiqiu
full_name: Dong, Yiqiu
last_name: Dong
- first_name: Anders
full_name: Bjorholm Dahl, Anders
last_name: Bjorholm Dahl
intvolume: ' 10302'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1703.03769
month: '06'
oa: 1
oa_version: Submitted Version
page: 235 - 246
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_identifier:
isbn:
- 978-331958770-7
publication_status: published
publisher: Springer
publist_id: '7132'
quality_controlled: '1'
scopus_import: 1
status: public
title: A novel convex relaxation for non binary discrete tomography
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 10302
year: '2017'
...
---
_id: '992'
abstract:
- lang: eng
text: "An instance of the Constraint Satisfaction Problem (CSP) is given by a finite
set of\r\nvariables, a finite domain of labels, and a set of constraints, each
constraint acting on\r\na subset of the variables. The goal is to find an assignment
of labels to its variables\r\nthat satisfies all constraints (or decide whether
one exists). If we allow more general\r\n“soft” constraints, which come with (possibly
infinite) costs of particular assignments,\r\nwe obtain instances from a richer
class called Valued Constraint Satisfaction Problem\r\n(VCSP). There the goal
is to find an assignment with minimum total cost.\r\nIn this thesis, we focus
(assuming that P\r\n6\r\n=\r\nNP) on classifying computational com-\r\nplexity
of CSPs and VCSPs under certain restricting conditions. Two results are the core\r\ncontent
of the work. In one of them, we consider VCSPs parametrized by a constraint\r\nlanguage,
that is the set of “soft” constraints allowed to form the instances, and finish\r\nthe
complexity classification modulo (missing pieces of) complexity classification
for\r\nanalogously parametrized CSP. The other result is a generalization of Edmonds’
perfect\r\nmatching algorithm. This generalization contributes to complexity classfications
in two\r\nways. First, it gives a new (largest known) polynomial-time solvable
class of Boolean\r\nCSPs in which every variable may appear in at most two constraints
and second, it\r\nsettles full classification of Boolean CSPs with planar drawing
(again parametrized by a\r\nconstraint language)."
acknowledgement: FP7/2007-2013/ERC grant agreement no 616160
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: Rolinek M. Complexity of constraint satisfaction. 2017. doi:10.15479/AT:ISTA:th_815
apa: Rolinek, M. (2017). Complexity of constraint satisfaction. Institute
of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_815
chicago: Rolinek, Michal. “Complexity of Constraint Satisfaction.” Institute of
Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_815.
ieee: M. Rolinek, “Complexity of constraint satisfaction,” Institute of Science
and Technology Austria, 2017.
ista: Rolinek M. 2017. Complexity of constraint satisfaction. Institute of Science
and Technology Austria.
mla: Rolinek, Michal. Complexity of Constraint Satisfaction. Institute of
Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_815.
short: M. Rolinek, Complexity of Constraint Satisfaction, Institute of Science and
Technology Austria, 2017.
date_created: 2018-12-11T11:49:35Z
date_published: 2017-05-01T00:00:00Z
date_updated: 2023-09-07T12:05:41Z
day: '01'
ddc:
- '004'
degree_awarded: PhD
department:
- _id: VlKo
doi: 10.15479/AT:ISTA:th_815
ec_funded: 1
file:
- access_level: open_access
checksum: 81761fb939acb7585c36629f765b4373
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:07:55Z
date_updated: 2020-07-14T12:48:18Z
file_id: '4654'
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file_size: 786145
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content_type: application/zip
creator: dernst
date_created: 2019-04-05T08:43:24Z
date_updated: 2020-07-14T12:48:18Z
file_id: '6208'
file_name: 2017_Thesis_Rolinek_source.zip
file_size: 5936337
relation: source_file
file_date_updated: 2020-07-14T12:48:18Z
has_accepted_license: '1'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
page: '97'
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
publist_id: '6407'
pubrep_id: '815'
status: public
supervisor:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
title: Complexity of constraint satisfaction
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2017'
...
---
_id: '1192'
abstract:
- lang: eng
text: The main result of this paper is a generalization of the classical blossom
algorithm for finding perfect matchings. Our algorithm can efficiently solve Boolean
CSPs where each variable appears in exactly two constraints (we call it edge CSP)
and all constraints are even Δ-matroid relations (represented by lists of tuples).
As a consequence of this, we settle the complexity classification of planar Boolean
CSPs started by Dvorak and Kupec. Knowing that edge CSP is tractable for even
Δ-matroid constraints allows us to extend the tractability result to a larger
class of Δ-matroids that includes many classes that were known to be tractable
before, namely co-independent, compact, local and binary.
article_processing_charge: No
author:
- first_name: Alexandr
full_name: Kazda, Alexandr
id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87
last_name: Kazda
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: 'Kazda A, Kolmogorov V, Rolinek M. Even delta-matroids and the complexity of
planar Boolean CSPs. In: SIAM; 2017:307-326. doi:10.1137/1.9781611974782.20'
apa: 'Kazda, A., Kolmogorov, V., & Rolinek, M. (2017). Even delta-matroids and
the complexity of planar Boolean CSPs (pp. 307–326). Presented at the SODA: Symposium
on Discrete Algorithms, Barcelona, Spain: SIAM. https://doi.org/10.1137/1.9781611974782.20'
chicago: Kazda, Alexandr, Vladimir Kolmogorov, and Michal Rolinek. “Even Delta-Matroids
and the Complexity of Planar Boolean CSPs,” 307–26. SIAM, 2017. https://doi.org/10.1137/1.9781611974782.20.
ieee: 'A. Kazda, V. Kolmogorov, and M. Rolinek, “Even delta-matroids and the complexity
of planar Boolean CSPs,” presented at the SODA: Symposium on Discrete Algorithms,
Barcelona, Spain, 2017, pp. 307–326.'
ista: 'Kazda A, Kolmogorov V, Rolinek M. 2017. Even delta-matroids and the complexity
of planar Boolean CSPs. SODA: Symposium on Discrete Algorithms, 307–326.'
mla: Kazda, Alexandr, et al. Even Delta-Matroids and the Complexity of Planar
Boolean CSPs. SIAM, 2017, pp. 307–26, doi:10.1137/1.9781611974782.20.
short: A. Kazda, V. Kolmogorov, M. Rolinek, in:, SIAM, 2017, pp. 307–326.
conference:
end_date: 2017-01019
location: Barcelona, Spain
name: 'SODA: Symposium on Discrete Algorithms'
start_date: 2017-01-16
date_created: 2018-12-11T11:50:38Z
date_published: 2017-01-01T00:00:00Z
date_updated: 2023-09-20T11:20:26Z
day: '01'
department:
- _id: VlKo
doi: 10.1137/1.9781611974782.20
ec_funded: 1
external_id:
isi:
- '000426965800020'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1602.03124
month: '01'
oa: 1
oa_version: Submitted Version
page: 307 - 326
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_identifier:
isbn:
- 978-161197478-2
publication_status: published
publisher: SIAM
publist_id: '6159'
quality_controlled: '1'
related_material:
record:
- id: '6032'
relation: later_version
status: public
status: public
title: Even delta-matroids and the complexity of planar Boolean CSPs
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2017'
...
---
_id: '916'
abstract:
- lang: eng
text: We study the quadratic assignment problem, in computer vision also known as
graph matching. Two leading solvers for this problem optimize the Lagrange decomposition
duals with sub-gradient and dual ascent (also known as message passing) updates.
We explore this direction further and propose several additional Lagrangean relaxations
of the graph matching problem along with corresponding algorithms, which are all
based on a common dual ascent framework. Our extensive empirical evaluation gives
several theoretical insights and suggests a new state-of-the-art anytime solver
for the considered problem. Our improvement over state-of-the-art is particularly
visible on a new dataset with large-scale sparse problem instances containing
more than 500 graph nodes each.
article_processing_charge: No
author:
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Carsten
full_name: Rother, Carsten
last_name: Rother
- first_name: Carsten
full_name: Abu Alhaija, Carsten
last_name: Abu Alhaija
- first_name: Dagmar
full_name: Kainmueller, Dagmar
last_name: Kainmueller
- first_name: Bogdan
full_name: Savchynskyy, Bogdan
last_name: Savchynskyy
citation:
ama: 'Swoboda P, Rother C, Abu Alhaija C, Kainmueller D, Savchynskyy B. A study
of lagrangean decompositions and dual ascent solvers for graph matching. In: Vol
2017. IEEE; 2017:7062-7071. doi:10.1109/CVPR.2017.747'
apa: 'Swoboda, P., Rother, C., Abu Alhaija, C., Kainmueller, D., & Savchynskyy,
B. (2017). A study of lagrangean decompositions and dual ascent solvers for graph
matching (Vol. 2017, pp. 7062–7071). Presented at the CVPR: Computer Vision and
Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.747'
chicago: Swoboda, Paul, Carsten Rother, Carsten Abu Alhaija, Dagmar Kainmueller,
and Bogdan Savchynskyy. “A Study of Lagrangean Decompositions and Dual Ascent
Solvers for Graph Matching,” 2017:7062–71. IEEE, 2017. https://doi.org/10.1109/CVPR.2017.747.
ieee: 'P. Swoboda, C. Rother, C. Abu Alhaija, D. Kainmueller, and B. Savchynskyy,
“A study of lagrangean decompositions and dual ascent solvers for graph matching,”
presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA,
United States, 2017, vol. 2017, pp. 7062–7071.'
ista: 'Swoboda P, Rother C, Abu Alhaija C, Kainmueller D, Savchynskyy B. 2017. A
study of lagrangean decompositions and dual ascent solvers for graph matching.
CVPR: Computer Vision and Pattern Recognition vol. 2017, 7062–7071.'
mla: Swoboda, Paul, et al. A Study of Lagrangean Decompositions and Dual Ascent
Solvers for Graph Matching. Vol. 2017, IEEE, 2017, pp. 7062–71, doi:10.1109/CVPR.2017.747.
short: P. Swoboda, C. Rother, C. Abu Alhaija, D. Kainmueller, B. Savchynskyy, in:,
IEEE, 2017, pp. 7062–7071.
conference:
end_date: 2017-07-26
location: Honolulu, HA, United States
name: 'CVPR: Computer Vision and Pattern Recognition'
start_date: 2017-07-21
date_created: 2018-12-11T11:49:11Z
date_published: 2017-01-01T00:00:00Z
date_updated: 2023-09-26T15:41:40Z
day: '01'
ddc:
- '000'
department:
- _id: VlKo
doi: 10.1109/CVPR.2017.747
ec_funded: 1
external_id:
isi:
- '000418371407018'
file:
- access_level: open_access
checksum: e38a2740daad1ea178465843b5072906
content_type: application/pdf
creator: dernst
date_created: 2019-01-18T12:49:38Z
date_updated: 2020-07-14T12:48:15Z
file_id: '5848'
file_name: 2017_CVPR_Swoboda2.pdf
file_size: 944332
relation: main_file
file_date_updated: 2020-07-14T12:48:15Z
has_accepted_license: '1'
intvolume: ' 2017'
isi: 1
language:
- iso: eng
month: '01'
oa: 1
oa_version: Submitted Version
page: 7062-7071
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_identifier:
isbn:
- 978-153860457-1
publication_status: published
publisher: IEEE
publist_id: '6525'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A study of lagrangean decompositions and dual ascent solvers for graph matching
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2017
year: '2017'
...
---
_id: '915'
abstract:
- lang: eng
text: We propose a dual decomposition and linear program relaxation of the NP-hard
minimum cost multicut problem. Unlike other polyhedral relaxations of the multicut
polytope, it is amenable to efficient optimization by message passing. Like other
polyhedral relaxations, it can be tightened efficiently by cutting planes. We
define an algorithm that alternates between message passing and efficient separation
of cycle- and odd-wheel inequalities. This algorithm is more efficient than state-of-the-art
algorithms based on linear programming, including algorithms written in the framework
of leading commercial software, as we show in experiments with large instances
of the problem from applications in computer vision, biomedical image analysis
and data mining.
article_processing_charge: No
author:
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Bjoern
full_name: Andres, Bjoern
last_name: Andres
citation:
ama: 'Swoboda P, Andres B. A message passing algorithm for the minimum cost multicut
problem. In: Vol 2017. IEEE; 2017:4990-4999. doi:10.1109/CVPR.2017.530'
apa: 'Swoboda, P., & Andres, B. (2017). A message passing algorithm for the
minimum cost multicut problem (Vol. 2017, pp. 4990–4999). Presented at the CVPR:
Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.530'
chicago: Swoboda, Paul, and Bjoern Andres. “A Message Passing Algorithm for the
Minimum Cost Multicut Problem,” 2017:4990–99. IEEE, 2017. https://doi.org/10.1109/CVPR.2017.530.
ieee: 'P. Swoboda and B. Andres, “A message passing algorithm for the minimum cost
multicut problem,” presented at the CVPR: Computer Vision and Pattern Recognition,
Honolulu, HA, United States, 2017, vol. 2017, pp. 4990–4999.'
ista: 'Swoboda P, Andres B. 2017. A message passing algorithm for the minimum cost
multicut problem. CVPR: Computer Vision and Pattern Recognition vol. 2017, 4990–4999.'
mla: Swoboda, Paul, and Bjoern Andres. A Message Passing Algorithm for the Minimum
Cost Multicut Problem. Vol. 2017, IEEE, 2017, pp. 4990–99, doi:10.1109/CVPR.2017.530.
short: P. Swoboda, B. Andres, in:, IEEE, 2017, pp. 4990–4999.
conference:
end_date: 2017-07-26
location: Honolulu, HA, United States
name: 'CVPR: Computer Vision and Pattern Recognition'
start_date: 2017-07-21
date_created: 2018-12-11T11:49:11Z
date_published: 2017-07-01T00:00:00Z
date_updated: 2023-09-26T15:43:27Z
day: '01'
ddc:
- '000'
department:
- _id: VlKo
doi: 10.1109/CVPR.2017.530
ec_funded: 1
external_id:
isi:
- '000418371405009'
file:
- access_level: open_access
checksum: 7e51dacefa693574581a32da3eff63dc
content_type: application/pdf
creator: dernst
date_created: 2019-01-18T12:52:46Z
date_updated: 2020-07-14T12:48:15Z
file_id: '5849'
file_name: Swoboda_A_Message_Passing_CVPR_2017_paper.pdf
file_size: 883264
relation: main_file
file_date_updated: 2020-07-14T12:48:15Z
has_accepted_license: '1'
intvolume: ' 2017'
isi: 1
language:
- iso: eng
month: '07'
oa: 1
oa_version: Submitted Version
page: 4990-4999
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_identifier:
isbn:
- 978-153860457-1
publication_status: published
publisher: IEEE
publist_id: '6526'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A message passing algorithm for the minimum cost multicut problem
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2017
year: '2017'
...
---
_id: '917'
abstract:
- lang: eng
text: We propose a general dual ascent framework for Lagrangean decomposition
of combinatorial problems. Although methods of this type have shown their efficiency
for a number of problems, so far there was no general algorithm applicable to
multiple problem types. In this work, we propose such a general algorithm. It
depends on several parameters, which can be used to optimize its performance in
each particular setting. We demonstrate efficacy of our method on graph matching
and multicut problems, where it outperforms state-of-the-art solvers including
those based on subgradient optimization and off-the-shelf linear programming solvers.
article_processing_charge: No
author:
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
- first_name: Jan
full_name: Kuske, Jan
last_name: Kuske
- first_name: Bogdan
full_name: Savchynskyy, Bogdan
last_name: Savchynskyy
citation:
ama: 'Swoboda P, Kuske J, Savchynskyy B. A dual ascent framework for Lagrangean
decomposition of combinatorial problems. In: Vol 2017. IEEE; 2017:4950-4960. doi:10.1109/CVPR.2017.526'
apa: 'Swoboda, P., Kuske, J., & Savchynskyy, B. (2017). A dual ascent framework
for Lagrangean decomposition of combinatorial problems (Vol. 2017, pp. 4950–4960).
Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA,
United States: IEEE. https://doi.org/10.1109/CVPR.2017.526'
chicago: Swoboda, Paul, Jan Kuske, and Bogdan Savchynskyy. “A Dual Ascent Framework
for Lagrangean Decomposition of Combinatorial Problems,” 2017:4950–60. IEEE, 2017.
https://doi.org/10.1109/CVPR.2017.526.
ieee: 'P. Swoboda, J. Kuske, and B. Savchynskyy, “A dual ascent framework for Lagrangean
decomposition of combinatorial problems,” presented at the CVPR: Computer Vision
and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 4950–4960.'
ista: 'Swoboda P, Kuske J, Savchynskyy B. 2017. A dual ascent framework for Lagrangean
decomposition of combinatorial problems. CVPR: Computer Vision and Pattern Recognition
vol. 2017, 4950–4960.'
mla: Swoboda, Paul, et al. A Dual Ascent Framework for Lagrangean Decomposition
of Combinatorial Problems. Vol. 2017, IEEE, 2017, pp. 4950–60, doi:10.1109/CVPR.2017.526.
short: P. Swoboda, J. Kuske, B. Savchynskyy, in:, IEEE, 2017, pp. 4950–4960.
conference:
end_date: 2017-07-26
location: Honolulu, HA, United States
name: 'CVPR: Computer Vision and Pattern Recognition'
start_date: 2017-07-21
date_created: 2018-12-11T11:49:11Z
date_published: 2017-07-01T00:00:00Z
date_updated: 2023-09-26T15:41:11Z
day: '01'
ddc:
- '000'
department:
- _id: VlKo
doi: 10.1109/CVPR.2017.526
ec_funded: 1
external_id:
isi:
- '000418371405005'
file:
- access_level: open_access
checksum: 72fd291046bd8e5717961bd68f6b6f03
content_type: application/pdf
creator: dernst
date_created: 2019-01-18T12:45:55Z
date_updated: 2020-07-14T12:48:15Z
file_id: '5847'
file_name: 2017_CVPR_Swoboda.pdf
file_size: 898652
relation: main_file
file_date_updated: 2020-07-14T12:48:15Z
has_accepted_license: '1'
intvolume: ' 2017'
isi: 1
language:
- iso: eng
month: '07'
oa: 1
oa_version: Submitted Version
page: 4950-4960
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_identifier:
isbn:
- 978-153860457-1
publication_status: published
publisher: IEEE
publist_id: '6524'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A dual ascent framework for Lagrangean decomposition of combinatorial problems
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 2017
year: '2017'
...
---
_id: '274'
abstract:
- lang: eng
text: We consider the problem of estimating the partition function Z(β)=∑xexp(−β(H(x))
of a Gibbs distribution with a Hamilton H(⋅), or more precisely the logarithm
of the ratio q=lnZ(0)/Z(β). It has been recently shown how to approximate q with
high probability assuming the existence of an oracle that produces samples from
the Gibbs distribution for a given parameter value in [0,β]. The current best
known approach due to Huber [9] uses O(qlnn⋅[lnq+lnlnn+ε−2]) oracle calls on average
where ε is the desired accuracy of approximation and H(⋅) is assumed to lie in
{0}∪[1,n]. We improve the complexity to O(qlnn⋅ε−2) oracle calls. We also show
that the same complexity can be achieved if exact oracles are replaced with approximate
sampling oracles that are within O(ε2qlnn) variation distance from exact oracles.
Finally, we prove a lower bound of Ω(q⋅ε−2) oracle calls under a natural model
of computation.
article_processing_charge: No
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Kolmogorov V. A faster approximation algorithm for the Gibbs partition function.
In: Proceedings of the 31st Conference On Learning Theory. Vol 75. ML Research
Press; 2017:228-249.'
apa: Kolmogorov, V. (2017). A faster approximation algorithm for the Gibbs partition
function. In Proceedings of the 31st Conference On Learning Theory (Vol.
75, pp. 228–249). ML Research Press.
chicago: Kolmogorov, Vladimir. “A Faster Approximation Algorithm for the Gibbs Partition
Function.” In Proceedings of the 31st Conference On Learning Theory, 75:228–49.
ML Research Press, 2017.
ieee: V. Kolmogorov, “A faster approximation algorithm for the Gibbs partition function,”
in Proceedings of the 31st Conference On Learning Theory, 2017, vol. 75,
pp. 228–249.
ista: 'Kolmogorov V. 2017. A faster approximation algorithm for the Gibbs partition
function. Proceedings of the 31st Conference On Learning Theory. COLT: Annual
Conference on Learning Theory vol. 75, 228–249.'
mla: Kolmogorov, Vladimir. “A Faster Approximation Algorithm for the Gibbs Partition
Function.” Proceedings of the 31st Conference On Learning Theory, vol.
75, ML Research Press, 2017, pp. 228–49.
short: V. Kolmogorov, in:, Proceedings of the 31st Conference On Learning Theory,
ML Research Press, 2017, pp. 228–249.
conference:
end_date: 2018-07-09
name: 'COLT: Annual Conference on Learning Theory '
start_date: 2018-07-06
date_created: 2018-12-11T11:45:33Z
date_published: 2017-12-27T00:00:00Z
date_updated: 2023-10-17T12:32:13Z
day: '27'
ddc:
- '510'
department:
- _id: VlKo
ec_funded: 1
external_id:
arxiv:
- '1608.04223'
file:
- access_level: open_access
checksum: 89db06a0e8083524449cb59b56bf4e5b
content_type: application/pdf
creator: dernst
date_created: 2020-05-12T09:23:27Z
date_updated: 2020-07-14T12:45:45Z
file_id: '7820'
file_name: 2018_PMLR_Kolmogorov.pdf
file_size: 408974
relation: main_file
file_date_updated: 2020-07-14T12:45:45Z
has_accepted_license: '1'
intvolume: ' 75'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: 228-249
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: Proceedings of the 31st Conference On Learning Theory
publication_status: published
publisher: ML Research Press
publist_id: '7628'
quality_controlled: '1'
status: public
title: A faster approximation algorithm for the Gibbs partition function
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 75
year: '2017'
...
---
_id: '5561'
abstract:
- lang: eng
text: 'Graph matching problems as described in "Active Graph Matching for Automatic
Joint Segmentation and Annotation of C. Elegans." by Kainmueller, Dagmar and Jug,
Florian and Rother, Carsten and Myers, Gene, MICCAI 2014. Problems are in OpenGM2
hdf5 format (see http://hciweb2.iwr.uni-heidelberg.de/opengm/) and a custom text
format used by the feature matching solver described in "Feature Correspondence
via Graph Matching: Models and Global Optimization." by Lorenzo Torresani, Vladimir
Kolmogorov and Carsten Rother, ECCV 2008, code at http://pub.ist.ac.at/~vnk/software/GraphMatching-v1.02.src.zip. '
acknowledgement: We thank Vladimir Kolmogorov and Stephan Saalfeld forinspiring discussions.
article_processing_charge: No
author:
- first_name: Dagmar
full_name: Kainmueller, Dagmar
last_name: Kainmueller
- first_name: Florian
full_name: Jug, Florian
last_name: Jug
- first_name: Carsten
full_name: Rother, Carsten
last_name: Rother
- first_name: Gene
full_name: Meyers, Gene
last_name: Meyers
citation:
ama: Kainmueller D, Jug F, Rother C, Meyers G. Graph matching problems for annotating
C. Elegans. 2017. doi:10.15479/AT:ISTA:57
apa: Kainmueller, D., Jug, F., Rother, C., & Meyers, G. (2017). Graph matching
problems for annotating C. Elegans. Institute of Science and Technology Austria.
https://doi.org/10.15479/AT:ISTA:57
chicago: Kainmueller, Dagmar, Florian Jug, Carsten Rother, and Gene Meyers. “Graph
Matching Problems for Annotating C. Elegans.” Institute of Science and Technology
Austria, 2017. https://doi.org/10.15479/AT:ISTA:57.
ieee: D. Kainmueller, F. Jug, C. Rother, and G. Meyers, “Graph matching problems
for annotating C. Elegans.” Institute of Science and Technology Austria, 2017.
ista: Kainmueller D, Jug F, Rother C, Meyers G. 2017. Graph matching problems for
annotating C. Elegans, Institute of Science and Technology Austria, 10.15479/AT:ISTA:57.
mla: Kainmueller, Dagmar, et al. Graph Matching Problems for Annotating C. Elegans.
Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:57.
short: D. Kainmueller, F. Jug, C. Rother, G. Meyers, (2017).
datarep_id: '57'
date_created: 2018-12-12T12:31:32Z
date_published: 2017-02-13T00:00:00Z
date_updated: 2024-02-21T13:46:31Z
day: '13'
ddc:
- '000'
department:
- _id: VlKo
doi: 10.15479/AT:ISTA:57
file:
- access_level: open_access
checksum: 3dc3e1306a66028a34181ebef2923139
content_type: application/zip
creator: system
date_created: 2018-12-12T13:02:54Z
date_updated: 2020-07-14T12:47:03Z
file_id: '5614'
file_name: IST-2017-57-v1+1_wormMatchingProblems.zip
file_size: 327042819
relation: main_file
file_date_updated: 2020-07-14T12:47:03Z
has_accepted_license: '1'
keyword:
- graph matching
- feature matching
- QAP
- MAP-inference
month: '02'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
status: public
title: Graph matching problems for annotating C. Elegans
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2017'
...
---
_id: '1231'
abstract:
- lang: eng
text: 'We study the time-and memory-complexities of the problem of computing labels
of (multiple) randomly selected challenge-nodes in a directed acyclic graph. The
w-bit label of a node is the hash of the labels of its parents, and the hash function
is modeled as a random oracle. Specific instances of this problem underlie both
proofs of space [Dziembowski et al. CRYPTO’15] as well as popular memory-hard
functions like scrypt. As our main tool, we introduce the new notion of a probabilistic
parallel entangled pebbling game, a new type of combinatorial pebbling game on
a graph, which is closely related to the labeling game on the same graph. As a
first application of our framework, we prove that for scrypt, when the underlying
hash function is invoked n times, the cumulative memory complexity (CMC) (a notion
recently introduced by Alwen and Serbinenko (STOC’15) to capture amortized memory-hardness
for parallel adversaries) is at least Ω(w · (n/ log(n))2). This bound holds for
adversaries that can store many natural functions of the labels (e.g., linear
combinations), but still not arbitrary functions thereof. We then introduce and
study a combinatorial quantity, and show how a sufficiently small upper bound
on it (which we conjecture) extends our CMC bound for scrypt to hold against arbitrary
adversaries. We also show that such an upper bound solves the main open problem
for proofs-of-space protocols: namely, establishing that the time complexity of
computing the label of a random node in a graph on n nodes (given an initial kw-bit
state) reduces tightly to the time complexity for black pebbling on the same graph
(given an initial k-node pebbling).'
acknowledgement: "Joël Alwen, Chethan Kamath, and Krzysztof Pietrzak’s research is
partially supported by an ERC starting grant (259668-PSPC). Vladimir Kolmogorov
is partially supported by an ERC consolidator grant (616160-DOICV). Binyi Chen was
partially supported by NSF grants CNS-1423566 and CNS-1514526, and a gift from the
Gareatis Foundation. Stefano Tessaro was partially supported by NSF grants CNS-1423566,
CNS-1528178, a Hellman Fellowship, and the Glen and Susanne Culler Chair.\r\n\r\nThis
work was done in part while the authors were visiting the Simons Institute for the
Theory of Computing, supported by the Simons Foundation and by the DIMACS/Simons
Collaboration in Cryptography through NSF grant CNS-1523467."
alternative_title:
- LNCS
author:
- first_name: Joel F
full_name: Alwen, Joel F
id: 2A8DFA8C-F248-11E8-B48F-1D18A9856A87
last_name: Alwen
- first_name: Binyi
full_name: Chen, Binyi
last_name: Chen
- first_name: Chethan
full_name: Kamath Hosdurg, Chethan
id: 4BD3F30E-F248-11E8-B48F-1D18A9856A87
last_name: Kamath Hosdurg
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
- first_name: Stefano
full_name: Tessaro, Stefano
last_name: Tessaro
citation:
ama: 'Alwen JF, Chen B, Kamath Hosdurg C, Kolmogorov V, Pietrzak KZ, Tessaro S.
On the complexity of scrypt and proofs of space in the parallel random oracle
model. In: Vol 9666. Springer; 2016:358-387. doi:10.1007/978-3-662-49896-5_13'
apa: 'Alwen, J. F., Chen, B., Kamath Hosdurg, C., Kolmogorov, V., Pietrzak, K. Z.,
& Tessaro, S. (2016). On the complexity of scrypt and proofs of space in the
parallel random oracle model (Vol. 9666, pp. 358–387). Presented at the EUROCRYPT:
Theory and Applications of Cryptographic Techniques, Vienna, Austria: Springer.
https://doi.org/10.1007/978-3-662-49896-5_13'
chicago: Alwen, Joel F, Binyi Chen, Chethan Kamath Hosdurg, Vladimir Kolmogorov,
Krzysztof Z Pietrzak, and Stefano Tessaro. “On the Complexity of Scrypt and Proofs
of Space in the Parallel Random Oracle Model,” 9666:358–87. Springer, 2016. https://doi.org/10.1007/978-3-662-49896-5_13.
ieee: 'J. F. Alwen, B. Chen, C. Kamath Hosdurg, V. Kolmogorov, K. Z. Pietrzak, and
S. Tessaro, “On the complexity of scrypt and proofs of space in the parallel random
oracle model,” presented at the EUROCRYPT: Theory and Applications of Cryptographic
Techniques, Vienna, Austria, 2016, vol. 9666, pp. 358–387.'
ista: 'Alwen JF, Chen B, Kamath Hosdurg C, Kolmogorov V, Pietrzak KZ, Tessaro S.
2016. On the complexity of scrypt and proofs of space in the parallel random oracle
model. EUROCRYPT: Theory and Applications of Cryptographic Techniques, LNCS, vol.
9666, 358–387.'
mla: Alwen, Joel F., et al. On the Complexity of Scrypt and Proofs of Space in
the Parallel Random Oracle Model. Vol. 9666, Springer, 2016, pp. 358–87, doi:10.1007/978-3-662-49896-5_13.
short: J.F. Alwen, B. Chen, C. Kamath Hosdurg, V. Kolmogorov, K.Z. Pietrzak, S.
Tessaro, in:, Springer, 2016, pp. 358–387.
conference:
end_date: 2016-05-12
location: Vienna, Austria
name: 'EUROCRYPT: Theory and Applications of Cryptographic Techniques'
start_date: 2016-05-08
date_created: 2018-12-11T11:50:51Z
date_published: 2016-04-28T00:00:00Z
date_updated: 2021-01-12T06:49:15Z
day: '28'
department:
- _id: KrPi
- _id: VlKo
doi: 10.1007/978-3-662-49896-5_13
ec_funded: 1
intvolume: ' 9666'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2016/100
month: '04'
oa: 1
oa_version: Submitted Version
page: 358 - 387
project:
- _id: 258C570E-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '259668'
name: Provable Security for Physical Cryptography
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_status: published
publisher: Springer
publist_id: '6103'
quality_controlled: '1'
scopus_import: 1
status: public
title: On the complexity of scrypt and proofs of space in the parallel random oracle
model
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 9666
year: '2016'
...
---
_id: '1353'
abstract:
- lang: eng
text: We characterize absorption in finite idempotent algebras by means of Jónsson
absorption and cube term blockers. As an application we show that it is decidable
whether a given subset is an absorbing subuniverse of an algebra given by the
tables of its basic operations.
acknowledgement: 'Libor Barto and Alexandr Kazda were supported by the the Grant Agency
of the Czech Republic, grant GACR 13-01832S. '
author:
- first_name: Libor
full_name: Barto, Libor
last_name: Barto
- first_name: Alexandr
full_name: Kazda, Alexandr
id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87
last_name: Kazda
citation:
ama: Barto L, Kazda A. Deciding absorption. International Journal of Algebra
and Computation. 2016;26(5):1033-1060. doi:10.1142/S0218196716500430
apa: Barto, L., & Kazda, A. (2016). Deciding absorption. International Journal
of Algebra and Computation. World Scientific Publishing. https://doi.org/10.1142/S0218196716500430
chicago: Barto, Libor, and Alexandr Kazda. “Deciding Absorption.” International
Journal of Algebra and Computation. World Scientific Publishing, 2016. https://doi.org/10.1142/S0218196716500430.
ieee: L. Barto and A. Kazda, “Deciding absorption,” International Journal of
Algebra and Computation, vol. 26, no. 5. World Scientific Publishing, pp.
1033–1060, 2016.
ista: Barto L, Kazda A. 2016. Deciding absorption. International Journal of Algebra
and Computation. 26(5), 1033–1060.
mla: Barto, Libor, and Alexandr Kazda. “Deciding Absorption.” International Journal
of Algebra and Computation, vol. 26, no. 5, World Scientific Publishing, 2016,
pp. 1033–60, doi:10.1142/S0218196716500430.
short: L. Barto, A. Kazda, International Journal of Algebra and Computation 26 (2016)
1033–1060.
date_created: 2018-12-11T11:51:32Z
date_published: 2016-07-20T00:00:00Z
date_updated: 2021-01-12T06:50:06Z
day: '20'
department:
- _id: VlKo
doi: 10.1142/S0218196716500430
intvolume: ' 26'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1512.07009
month: '07'
oa: 1
oa_version: Preprint
page: 1033 - 1060
publication: International Journal of Algebra and Computation
publication_status: published
publisher: World Scientific Publishing
publist_id: '5893'
quality_controlled: '1'
scopus_import: 1
status: public
title: Deciding absorption
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 26
year: '2016'
...
---
_id: '1377'
abstract:
- lang: eng
text: We consider the problem of minimizing the continuous valued total variation
subject to different unary terms on trees and propose fast direct algorithms based
on dynamic programming to solve these problems. We treat both the convex and the
nonconvex case and derive worst-case complexities that are equal to or better
than existing methods. We show applications to total variation based two dimensional
image processing and computer vision problems based on a Lagrangian decomposition
approach. The resulting algorithms are very effcient, offer a high degree of parallelism,
and come along with memory requirements which are only in the order of the number
of image pixels.
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Thomas
full_name: Pock, Thomas
last_name: Pock
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: Kolmogorov V, Pock T, Rolinek M. Total variation on a tree. SIAM Journal
on Imaging Sciences. 2016;9(2):605-636. doi:10.1137/15M1010257
apa: Kolmogorov, V., Pock, T., & Rolinek, M. (2016). Total variation on a tree.
SIAM Journal on Imaging Sciences. Society for Industrial and Applied Mathematics
. https://doi.org/10.1137/15M1010257
chicago: Kolmogorov, Vladimir, Thomas Pock, and Michal Rolinek. “Total Variation
on a Tree.” SIAM Journal on Imaging Sciences. Society for Industrial and
Applied Mathematics , 2016. https://doi.org/10.1137/15M1010257.
ieee: V. Kolmogorov, T. Pock, and M. Rolinek, “Total variation on a tree,” SIAM
Journal on Imaging Sciences, vol. 9, no. 2. Society for Industrial and Applied
Mathematics , pp. 605–636, 2016.
ista: Kolmogorov V, Pock T, Rolinek M. 2016. Total variation on a tree. SIAM Journal
on Imaging Sciences. 9(2), 605–636.
mla: Kolmogorov, Vladimir, et al. “Total Variation on a Tree.” SIAM Journal on
Imaging Sciences, vol. 9, no. 2, Society for Industrial and Applied Mathematics
, 2016, pp. 605–36, doi:10.1137/15M1010257.
short: V. Kolmogorov, T. Pock, M. Rolinek, SIAM Journal on Imaging Sciences 9 (2016)
605–636.
date_created: 2018-12-11T11:51:40Z
date_published: 2016-05-03T00:00:00Z
date_updated: 2021-01-12T06:50:15Z
day: '03'
department:
- _id: VlKo
doi: 10.1137/15M1010257
ec_funded: 1
intvolume: ' 9'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1502.07770
month: '05'
oa: 1
oa_version: Preprint
page: 605 - 636
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: SIAM Journal on Imaging Sciences
publication_status: published
publisher: 'Society for Industrial and Applied Mathematics '
publist_id: '5834'
quality_controlled: '1'
scopus_import: 1
status: public
title: Total variation on a tree
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 9
year: '2016'
...
---
_id: '1612'
abstract:
- lang: eng
text: We prove that whenever A is a 3-conservative relational structure with only
binary and unary relations,then the algebra of polymorphisms of A either has no
Taylor operation (i.e.,CSP(A)is NP-complete),or it generates an SD(∧) variety
(i.e.,CSP(A)has bounded width).
author:
- first_name: Alexandr
full_name: Kazda, Alexandr
id: 3B32BAA8-F248-11E8-B48F-1D18A9856A87
last_name: Kazda
citation:
ama: Kazda A. CSP for binary conservative relational structures. Algebra Universalis.
2016;75(1):75-84. doi:10.1007/s00012-015-0358-8
apa: Kazda, A. (2016). CSP for binary conservative relational structures. Algebra
Universalis. Springer. https://doi.org/10.1007/s00012-015-0358-8
chicago: Kazda, Alexandr. “CSP for Binary Conservative Relational Structures.” Algebra
Universalis. Springer, 2016. https://doi.org/10.1007/s00012-015-0358-8.
ieee: A. Kazda, “CSP for binary conservative relational structures,” Algebra
Universalis, vol. 75, no. 1. Springer, pp. 75–84, 2016.
ista: Kazda A. 2016. CSP for binary conservative relational structures. Algebra
Universalis. 75(1), 75–84.
mla: Kazda, Alexandr. “CSP for Binary Conservative Relational Structures.” Algebra
Universalis, vol. 75, no. 1, Springer, 2016, pp. 75–84, doi:10.1007/s00012-015-0358-8.
short: A. Kazda, Algebra Universalis 75 (2016) 75–84.
date_created: 2018-12-11T11:53:01Z
date_published: 2016-02-01T00:00:00Z
date_updated: 2021-01-12T06:52:00Z
day: '01'
department:
- _id: VlKo
doi: 10.1007/s00012-015-0358-8
intvolume: ' 75'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1112.1099
month: '02'
oa: 1
oa_version: Preprint
page: 75 - 84
publication: Algebra Universalis
publication_status: published
publisher: Springer
publist_id: '5554'
quality_controlled: '1'
scopus_import: 1
status: public
title: CSP for binary conservative relational structures
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 75
year: '2016'
...
---
_id: '1193'
abstract:
- lang: eng
text: We consider the recent formulation of the Algorithmic Lovász Local Lemma [1],
[2] for finding objects that avoid "bad features", or "flaws".
It extends the Moser-Tardos resampling algorithm [3] to more general discrete
spaces. At each step the method picks a flaw present in the current state and
"resamples" it using a "resampling oracle" provided by the
user. However, it is less flexible than the Moser-Tardos method since [1], [2]
require a specific flaw selection rule, whereas [3] allows an arbitrary rule (and
thus can potentially be implemented more efficiently). We formulate a new "commutativity"
condition, and prove that it is sufficient for an arbitrary rule to work. It also
enables an efficient parallelization under an additional assumption. We then show
that existing resampling oracles for perfect matchings and permutations do satisfy
this condition. Finally, we generalize the precondition in [2] (in the case of
symmetric potential causality graphs). This unifies special cases that previously
were treated separately.
acknowledgement: European Unions Seventh Framework Programme (FP7/2007-2013)/ERC grant
agreement no 616160
article_number: '7782993'
article_processing_charge: No
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Kolmogorov V. Commutativity in the algorithmic Lovasz local lemma. In: Proceedings
- Annual IEEE Symposium on Foundations of Computer Science. Vol 2016-December.
IEEE; 2016. doi:10.1109/FOCS.2016.88'
apa: 'Kolmogorov, V. (2016). Commutativity in the algorithmic Lovasz local lemma.
In Proceedings - Annual IEEE Symposium on Foundations of Computer Science
(Vol. 2016–December). New Brunswick, NJ, USA : IEEE. https://doi.org/10.1109/FOCS.2016.88'
chicago: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovasz Local Lemma.”
In Proceedings - Annual IEEE Symposium on Foundations of Computer Science,
Vol. 2016–December. IEEE, 2016. https://doi.org/10.1109/FOCS.2016.88.
ieee: V. Kolmogorov, “Commutativity in the algorithmic Lovasz local lemma,” in Proceedings
- Annual IEEE Symposium on Foundations of Computer Science, New Brunswick,
NJ, USA , 2016, vol. 2016–December.
ista: 'Kolmogorov V. 2016. Commutativity in the algorithmic Lovasz local lemma.
Proceedings - Annual IEEE Symposium on Foundations of Computer Science. FOCS:
Foundations of Computer Science vol. 2016–December, 7782993.'
mla: Kolmogorov, Vladimir. “Commutativity in the Algorithmic Lovasz Local Lemma.”
Proceedings - Annual IEEE Symposium on Foundations of Computer Science,
vol. 2016–December, 7782993, IEEE, 2016, doi:10.1109/FOCS.2016.88.
short: V. Kolmogorov, in:, Proceedings - Annual IEEE Symposium on Foundations of
Computer Science, IEEE, 2016.
conference:
end_date: 2016-09-11
location: 'New Brunswick, NJ, USA '
name: 'FOCS: Foundations of Computer Science'
start_date: 2016-09-09
date_created: 2018-12-11T11:50:38Z
date_published: 2016-12-15T00:00:00Z
date_updated: 2023-09-19T14:24:57Z
day: '15'
department:
- _id: VlKo
doi: 10.1109/FOCS.2016.88
ec_funded: 1
external_id:
arxiv:
- '1506.08547'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1506.08547v7
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: Proceedings - Annual IEEE Symposium on Foundations of Computer Science
publication_status: published
publisher: IEEE
publist_id: '6158'
quality_controlled: '1'
related_material:
record:
- id: '5975'
relation: later_version
status: public
scopus_import: 1
status: public
title: Commutativity in the algorithmic Lovasz local lemma
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2016-December
year: '2016'
...
---
_id: '1794'
abstract:
- lang: eng
text: We consider Conditional random fields (CRFs) with pattern-based potentials
defined on a chain. In this model the energy of a string (labeling) (Formula presented.)
is the sum of terms over intervals [i, j] where each term is non-zero only if
the substring (Formula presented.) equals a prespecified pattern w. Such CRFs
can be naturally applied to many sequence tagging problems. We present efficient
algorithms for the three standard inference tasks in a CRF, namely computing (i)
the partition function, (ii) marginals, and (iii) computing the MAP. Their complexities
are respectively (Formula presented.), (Formula presented.) and (Formula presented.)
where L is the combined length of input patterns, (Formula presented.) is the
maximum length of a pattern, and D is the input alphabet. This improves on the
previous algorithms of Ye et al. (NIPS, 2009) whose complexities are respectively
(Formula presented.), (Formula presented.) and (Formula presented.), where (Formula
presented.) is the number of input patterns. In addition, we give an efficient
algorithm for sampling, and revisit the case of MAP with non-positive weights.
acknowledgement: This work has been partially supported by the European Research Council
under the European Unions Seventh Framework Programme (FP7/2007-2013)/ERC grant
agreement no. 616160.
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Rustem
full_name: Takhanov, Rustem
id: 2CCAC26C-F248-11E8-B48F-1D18A9856A87
last_name: Takhanov
citation:
ama: Kolmogorov V, Takhanov R. Inference algorithms for pattern-based CRFs on sequence
data. Algorithmica. 2016;76(1):17-46. doi:10.1007/s00453-015-0017-7
apa: Kolmogorov, V., & Takhanov, R. (2016). Inference algorithms for pattern-based
CRFs on sequence data. Algorithmica. Springer. https://doi.org/10.1007/s00453-015-0017-7
chicago: Kolmogorov, Vladimir, and Rustem Takhanov. “Inference Algorithms for Pattern-Based
CRFs on Sequence Data.” Algorithmica. Springer, 2016. https://doi.org/10.1007/s00453-015-0017-7.
ieee: V. Kolmogorov and R. Takhanov, “Inference algorithms for pattern-based CRFs
on sequence data,” Algorithmica, vol. 76, no. 1. Springer, pp. 17–46, 2016.
ista: Kolmogorov V, Takhanov R. 2016. Inference algorithms for pattern-based CRFs
on sequence data. Algorithmica. 76(1), 17–46.
mla: Kolmogorov, Vladimir, and Rustem Takhanov. “Inference Algorithms for Pattern-Based
CRFs on Sequence Data.” Algorithmica, vol. 76, no. 1, Springer, 2016, pp.
17–46, doi:10.1007/s00453-015-0017-7.
short: V. Kolmogorov, R. Takhanov, Algorithmica 76 (2016) 17–46.
date_created: 2018-12-11T11:54:02Z
date_published: 2016-09-01T00:00:00Z
date_updated: 2023-10-17T09:51:31Z
day: '01'
department:
- _id: VlKo
doi: 10.1007/s00453-015-0017-7
ec_funded: 1
external_id:
arxiv:
- '1210.0508'
intvolume: ' 76'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1210.0508
month: '09'
oa: 1
oa_version: Preprint
page: 17 - 46
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: Algorithmica
publication_status: published
publisher: Springer
publist_id: '5316'
quality_controlled: '1'
related_material:
record:
- id: '2272'
relation: earlier_version
status: public
scopus_import: 1
status: public
title: Inference algorithms for pattern-based CRFs on sequence data
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 76
year: '2016'
...
---
_id: '5557'
abstract:
- lang: eng
text: "Small synthetic discrete tomography problems.\r\nSizes are 32x32, 64z64 and
256x256.\r\nProjection angles are 2, 4, and 6.\r\nNumber of labels are 3 and 5."
article_processing_charge: No
author:
- first_name: Paul
full_name: Swoboda, Paul
id: 446560C6-F248-11E8-B48F-1D18A9856A87
last_name: Swoboda
citation:
ama: Swoboda P. Synthetic discrete tomography problems. 2016. doi:10.15479/AT:ISTA:46
apa: Swoboda, P. (2016). Synthetic discrete tomography problems. Institute of Science
and Technology Austria. https://doi.org/10.15479/AT:ISTA:46
chicago: Swoboda, Paul. “Synthetic Discrete Tomography Problems.” Institute of Science
and Technology Austria, 2016. https://doi.org/10.15479/AT:ISTA:46.
ieee: P. Swoboda, “Synthetic discrete tomography problems.” Institute of Science
and Technology Austria, 2016.
ista: Swoboda P. 2016. Synthetic discrete tomography problems, Institute of Science
and Technology Austria, 10.15479/AT:ISTA:46.
mla: Swoboda, Paul. Synthetic Discrete Tomography Problems. Institute of
Science and Technology Austria, 2016, doi:10.15479/AT:ISTA:46.
short: P. Swoboda, (2016).
contributor:
- contributor_type: data_collector
first_name: Jan
last_name: Kuske
datarep_id: '46'
date_created: 2018-12-12T12:31:31Z
date_published: 2016-09-20T00:00:00Z
date_updated: 2024-02-21T13:50:21Z
day: '20'
ddc:
- '006'
department:
- _id: VlKo
doi: 10.15479/AT:ISTA:46
file:
- access_level: open_access
checksum: aa5a16a0dc888da7186fb8fc45e88439
content_type: application/zip
creator: system
date_created: 2018-12-12T13:05:19Z
date_updated: 2020-07-14T12:47:02Z
file_id: '5645'
file_name: IST-2016-46-v1+1_discrete_tomography_synthetic.zip
file_size: 36058401
relation: main_file
file_date_updated: 2020-07-14T12:47:02Z
has_accepted_license: '1'
keyword:
- discrete tomography
month: '09'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
status: public
title: Synthetic discrete tomography problems
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2016'
...
---
_id: '1636'
abstract:
- lang: eng
text: "Constraint Satisfaction Problem (CSP) is a fundamental algorithmic problem
that appears in many areas of Computer Science. It can be equivalently stated
as computing a homomorphism R→ΓΓ between two relational structures, e.g. between
two directed graphs. Analyzing its complexity has been a prominent research direction,
especially for the fixed template CSPs where the right side ΓΓ is fixed and the
left side R is unconstrained.\r\n\r\nFar fewer results are known for the hybrid
setting that restricts both sides simultaneously. It assumes that R belongs to
a certain class of relational structures (called a structural restriction in this
paper). We study which structural restrictions are effective, i.e. there exists
a fixed template ΓΓ (from a certain class of languages) for which the problem
is tractable when R is restricted, and NP-hard otherwise. We provide a characterization
for structural restrictions that are closed under inverse homomorphisms. The criterion
is based on the chromatic number of a relational structure defined in this paper;
it generalizes the standard chromatic number of a graph.\r\n\r\nAs our main tool,
we use the algebraic machinery developed for fixed template CSPs. To apply it
to our case, we introduce a new construction called a “lifted language”. We also
give a characterization for structural restrictions corresponding to minor-closed
families of graphs, extend results to certain Valued CSPs (namely conservative
valued languages), and state implications for (valued) CSPs with ordered variables
and for the maximum weight independent set problem on some restricted families
of graphs."
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
- first_name: Rustem
full_name: Takhanov, Rustem
last_name: Takhanov
citation:
ama: 'Kolmogorov V, Rolinek M, Takhanov R. Effectiveness of structural restrictions
for hybrid CSPs. In: 26th International Symposium. Vol 9472. Springer Nature;
2015:566-577. doi:10.1007/978-3-662-48971-0_48'
apa: 'Kolmogorov, V., Rolinek, M., & Takhanov, R. (2015). Effectiveness of structural
restrictions for hybrid CSPs. In 26th International Symposium (Vol. 9472,
pp. 566–577). Nagoya, Japan: Springer Nature. https://doi.org/10.1007/978-3-662-48971-0_48'
chicago: Kolmogorov, Vladimir, Michal Rolinek, and Rustem Takhanov. “Effectiveness
of Structural Restrictions for Hybrid CSPs.” In 26th International Symposium,
9472:566–77. Springer Nature, 2015. https://doi.org/10.1007/978-3-662-48971-0_48.
ieee: V. Kolmogorov, M. Rolinek, and R. Takhanov, “Effectiveness of structural restrictions
for hybrid CSPs,” in 26th International Symposium, Nagoya, Japan, 2015,
vol. 9472, pp. 566–577.
ista: 'Kolmogorov V, Rolinek M, Takhanov R. 2015. Effectiveness of structural restrictions
for hybrid CSPs. 26th International Symposium. ISAAC: International Symposium
on Algorithms and Computation, LNCS, vol. 9472, 566–577.'
mla: Kolmogorov, Vladimir, et al. “Effectiveness of Structural Restrictions for
Hybrid CSPs.” 26th International Symposium, vol. 9472, Springer Nature,
2015, pp. 566–77, doi:10.1007/978-3-662-48971-0_48.
short: V. Kolmogorov, M. Rolinek, R. Takhanov, in:, 26th International Symposium,
Springer Nature, 2015, pp. 566–577.
conference:
end_date: 2015-12-11
location: Nagoya, Japan
name: 'ISAAC: International Symposium on Algorithms and Computation'
start_date: 2015-12-09
date_created: 2018-12-11T11:53:10Z
date_published: 2015-12-01T00:00:00Z
date_updated: 2022-02-01T15:12:35Z
day: '01'
department:
- _id: VlKo
doi: 10.1007/978-3-662-48971-0_48
ec_funded: 1
external_id:
arxiv:
- '1504.07067'
intvolume: ' 9472'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1504.07067
month: '12'
oa: 1
oa_version: Preprint
page: 566 - 577
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: 26th International Symposium
publication_identifier:
isbn:
- 978-3-662-48970-3
publication_status: published
publisher: Springer Nature
publist_id: '5519'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Effectiveness of structural restrictions for hybrid CSPs
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 9472
year: '2015'
...
---
_id: '1841'
abstract:
- lang: eng
text: We propose a new family of message passing techniques for MAP estimation in
graphical models which we call Sequential Reweighted Message Passing (SRMP). Special
cases include well-known techniques such as Min-Sum Diffusion (MSD) and a faster
Sequential Tree-Reweighted Message Passing (TRW-S). Importantly, our derivation
is simpler than the original derivation of TRW-S, and does not involve a decomposition
into trees. This allows easy generalizations. The new family of algorithms can
be viewed as a generalization of TRW-S from pairwise to higher-order graphical
models. We test SRMP on several real-world problems with promising results.
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: Kolmogorov V. A new look at reweighted message passing. IEEE Transactions
on Pattern Analysis and Machine Intelligence. 2015;37(5):919-930. doi:10.1109/TPAMI.2014.2363465
apa: Kolmogorov, V. (2015). A new look at reweighted message passing. IEEE Transactions
on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2014.2363465
chicago: Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” IEEE
Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2015. https://doi.org/10.1109/TPAMI.2014.2363465.
ieee: V. Kolmogorov, “A new look at reweighted message passing,” IEEE Transactions
on Pattern Analysis and Machine Intelligence, vol. 37, no. 5. IEEE, pp. 919–930,
2015.
ista: Kolmogorov V. 2015. A new look at reweighted message passing. IEEE Transactions
on Pattern Analysis and Machine Intelligence. 37(5), 919–930.
mla: Kolmogorov, Vladimir. “A New Look at Reweighted Message Passing.” IEEE Transactions
on Pattern Analysis and Machine Intelligence, vol. 37, no. 5, IEEE, 2015,
pp. 919–30, doi:10.1109/TPAMI.2014.2363465.
short: V. Kolmogorov, IEEE Transactions on Pattern Analysis and Machine Intelligence
37 (2015) 919–930.
date_created: 2018-12-11T11:54:18Z
date_published: 2015-05-01T00:00:00Z
date_updated: 2021-01-12T06:53:33Z
day: '01'
department:
- _id: VlKo
doi: 10.1109/TPAMI.2014.2363465
ec_funded: 1
intvolume: ' 37'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1309.5655
month: '05'
oa: 1
oa_version: Preprint
page: 919 - 930
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication: IEEE Transactions on Pattern Analysis and Machine Intelligence
publication_status: published
publisher: IEEE
publist_id: '5261'
quality_controlled: '1'
scopus_import: 1
status: public
title: A new look at reweighted message passing
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2015'
...
---
_id: '1859'
abstract:
- lang: eng
text: "Structural support vector machines (SSVMs) are amongst the best performing
models for structured computer vision tasks, such as semantic image segmentation
or human pose estimation. Training SSVMs, however, is computationally costly,
because it requires repeated calls to a structured prediction subroutine (called
\\emph{max-oracle}), which has to solve an optimization problem itself, e.g. a
graph cut.\r\nIn this work, we introduce a new algorithm for SSVM training that
is more efficient than earlier techniques when the max-oracle is computationally
expensive, as it is frequently the case in computer vision tasks. The main idea
is to (i) combine the recent stochastic Block-Coordinate Frank-Wolfe algorithm
with efficient hyperplane caching, and (ii) use an automatic selection rule for
deciding whether to call the exact max-oracle or to rely on an approximate one
based on the cached hyperplanes.\r\nWe show experimentally that this strategy
leads to faster convergence to the optimum with respect to the number of requires
oracle calls, and that this translates into faster convergence with respect to
the total runtime when the max-oracle is slow compared to the other steps of the
algorithm. "
author:
- first_name: Neel
full_name: Shah, Neel
id: 31ABAF80-F248-11E8-B48F-1D18A9856A87
last_name: Shah
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Shah N, Kolmogorov V, Lampert C. A multi-plane block-coordinate Frank-Wolfe
algorithm for training structural SVMs with a costly max-oracle. In: IEEE; 2015:2737-2745.
doi:10.1109/CVPR.2015.7298890'
apa: 'Shah, N., Kolmogorov, V., & Lampert, C. (2015). A multi-plane block-coordinate
Frank-Wolfe algorithm for training structural SVMs with a costly max-oracle (pp.
2737–2745). Presented at the CVPR: Computer Vision and Pattern Recognition, Boston,
MA, USA: IEEE. https://doi.org/10.1109/CVPR.2015.7298890'
chicago: Shah, Neel, Vladimir Kolmogorov, and Christoph Lampert. “A Multi-Plane
Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly
Max-Oracle,” 2737–45. IEEE, 2015. https://doi.org/10.1109/CVPR.2015.7298890.
ieee: 'N. Shah, V. Kolmogorov, and C. Lampert, “A multi-plane block-coordinate Frank-Wolfe
algorithm for training structural SVMs with a costly max-oracle,” presented at
the CVPR: Computer Vision and Pattern Recognition, Boston, MA, USA, 2015, pp.
2737–2745.'
ista: 'Shah N, Kolmogorov V, Lampert C. 2015. A multi-plane block-coordinate Frank-Wolfe
algorithm for training structural SVMs with a costly max-oracle. CVPR: Computer
Vision and Pattern Recognition, 2737–2745.'
mla: Shah, Neel, et al. A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm
for Training Structural SVMs with a Costly Max-Oracle. IEEE, 2015, pp. 2737–45,
doi:10.1109/CVPR.2015.7298890.
short: N. Shah, V. Kolmogorov, C. Lampert, in:, IEEE, 2015, pp. 2737–2745.
conference:
end_date: 2015-06-12
location: Boston, MA, USA
name: 'CVPR: Computer Vision and Pattern Recognition'
start_date: 2015-06-07
date_created: 2018-12-11T11:54:24Z
date_published: 2015-06-01T00:00:00Z
date_updated: 2021-01-12T06:53:40Z
day: '01'
department:
- _id: VlKo
- _id: ChLa
doi: 10.1109/CVPR.2015.7298890
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1408.6804
month: '06'
oa: 1
oa_version: Preprint
page: 2737 - 2745
project:
- _id: 2532554C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '308036'
name: Lifelong Learning of Visual Scene Understanding
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_status: published
publisher: IEEE
publist_id: '5240'
quality_controlled: '1'
scopus_import: 1
status: public
title: A multi-plane block-coordinate Frank-Wolfe algorithm for training structural
SVMs with a costly max-oracle
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2015'
...
---
_id: '2271'
abstract:
- lang: eng
text: "A class of valued constraint satisfaction problems (VCSPs) is characterised
by a valued constraint language, a fixed set of cost functions on a finite domain.
Finite-valued constraint languages contain functions that take on rational costs
and general-valued constraint languages contain functions that take on rational
or infinite costs. An instance of the problem is specified by a sum of functions
from the language with the goal to minimise the sum. This framework includes and
generalises well-studied constraint satisfaction problems (CSPs) and maximum constraint
satisfaction problems (Max-CSPs).\r\nOur main result is a precise algebraic characterisation
of valued constraint languages whose instances can be solved exactly by the basic
linear programming relaxation (BLP). For a general-valued constraint language
Γ, BLP is a decision procedure for Γ if and only if Γ admits a symmetric fractional
polymorphism of every arity. For a finite-valued constraint language Γ, BLP is
a decision procedure if and only if Γ admits a symmetric fractional polymorphism
of some arity, or equivalently, if Γ admits a symmetric fractional polymorphism
of arity 2.\r\nUsing these results, we obtain tractability of several novel and
previously widely-open classes of VCSPs, including problems over valued constraint
languages that are: (1) submodular on arbitrary lattices; (2) bisubmodular (also
known as k-submodular) on arbitrary finite domains; (3) weakly (and hence strongly)
tree-submodular on arbitrary trees. "
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Johan
full_name: Thapper, Johan
last_name: Thapper
- first_name: Stanislav
full_name: Živný, Stanislav
last_name: Živný
citation:
ama: Kolmogorov V, Thapper J, Živný S. The power of linear programming for general-valued
CSPs. SIAM Journal on Computing. 2015;44(1):1-36. doi:10.1137/130945648
apa: Kolmogorov, V., Thapper, J., & Živný, S. (2015). The power of linear programming
for general-valued CSPs. SIAM Journal on Computing. SIAM. https://doi.org/10.1137/130945648
chicago: Kolmogorov, Vladimir, Johan Thapper, and Stanislav Živný. “The Power of
Linear Programming for General-Valued CSPs.” SIAM Journal on Computing.
SIAM, 2015. https://doi.org/10.1137/130945648.
ieee: V. Kolmogorov, J. Thapper, and S. Živný, “The power of linear programming
for general-valued CSPs,” SIAM Journal on Computing, vol. 44, no. 1. SIAM,
pp. 1–36, 2015.
ista: Kolmogorov V, Thapper J, Živný S. 2015. The power of linear programming for
general-valued CSPs. SIAM Journal on Computing. 44(1), 1–36.
mla: Kolmogorov, Vladimir, et al. “The Power of Linear Programming for General-Valued
CSPs.” SIAM Journal on Computing, vol. 44, no. 1, SIAM, 2015, pp. 1–36,
doi:10.1137/130945648.
short: V. Kolmogorov, J. Thapper, S. Živný, SIAM Journal on Computing 44 (2015)
1–36.
date_created: 2018-12-11T11:56:41Z
date_published: 2015-02-01T00:00:00Z
date_updated: 2023-02-23T10:46:30Z
day: '01'
department:
- _id: VlKo
doi: 10.1137/130945648
external_id:
arxiv:
- '1311.4219'
intvolume: ' 44'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1311.4219
month: '02'
oa: 1
oa_version: Preprint
page: 1 - 36
publication: SIAM Journal on Computing
publication_status: published
publisher: SIAM
publist_id: '4673'
quality_controlled: '1'
related_material:
record:
- id: '2518'
relation: earlier_version
status: public
scopus_import: 1
status: public
title: The power of linear programming for general-valued CSPs
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 44
year: '2015'
...
---
_id: '1637'
abstract:
- lang: eng
text: An instance of the Valued Constraint Satisfaction Problem (VCSP) is given
by a finite set of variables, a finite domain of labels, and a sum of functions,
each function depending on a subset of the variables. Each function can take finite
values specifying costs of assignments of labels to its variables or the infinite
value, which indicates an infeasible assignment. The goal is to find an assignment
of labels to the variables that minimizes the sum. We study, assuming that P ≠
NP, how the complexity of this very general problem depends on the set of functions
allowed in the instances, the so-called constraint language. The case when all
allowed functions take values in {0, ∞} corresponds to ordinary CSPs, where one
deals only with the feasibility issue and there is no optimization. This case
is the subject of the Algebraic CSP Dichotomy Conjecture predicting for which
constraint languages CSPs are tractable (i.e. solvable in polynomial time) and
for which NP-hard. The case when all allowed functions take only finite values
corresponds to finite-valued CSP, where the feasibility aspect is trivial and
one deals only with the optimization issue. The complexity of finite-valued CSPs
was fully classified by Thapper and Zivny. An algebraic necessary condition for
tractability of a general-valued CSP with a fixed constraint language was recently
given by Kozik and Ochremiak. As our main result, we prove that if a constraint
language satisfies this algebraic necessary condition, and the feasibility CSP
(i.e. the problem of deciding whether a given instance has a feasible solution)
corresponding to the VCSP with this language is tractable, then the VCSP is tractable.
The algorithm is a simple combination of the assumed algorithm for the feasibility
CSP and the standard LP relaxation. As a corollary, we obtain that a dichotomy
for ordinary CSPs would imply a dichotomy for general-valued CSPs.
alternative_title:
- 56th Annual Symposium on Foundations of Computer Science
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Andrei
full_name: Krokhin, Andrei
last_name: Krokhin
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: 'Kolmogorov V, Krokhin A, Rolinek M. The complexity of general-valued CSPs.
In: IEEE; 2015:1246-1258. doi:10.1109/FOCS.2015.80'
apa: 'Kolmogorov, V., Krokhin, A., & Rolinek, M. (2015). The complexity of general-valued
CSPs (pp. 1246–1258). Presented at the FOCS: Foundations of Computer Science,
Berkeley, CA, United States: IEEE. https://doi.org/10.1109/FOCS.2015.80'
chicago: Kolmogorov, Vladimir, Andrei Krokhin, and Michal Rolinek. “The Complexity
of General-Valued CSPs,” 1246–58. IEEE, 2015. https://doi.org/10.1109/FOCS.2015.80.
ieee: 'V. Kolmogorov, A. Krokhin, and M. Rolinek, “The complexity of general-valued
CSPs,” presented at the FOCS: Foundations of Computer Science, Berkeley, CA, United
States, 2015, pp. 1246–1258.'
ista: 'Kolmogorov V, Krokhin A, Rolinek M. 2015. The complexity of general-valued
CSPs. FOCS: Foundations of Computer Science, 56th Annual Symposium on Foundations
of Computer Science, , 1246–1258.'
mla: Kolmogorov, Vladimir, et al. The Complexity of General-Valued CSPs.
IEEE, 2015, pp. 1246–58, doi:10.1109/FOCS.2015.80.
short: V. Kolmogorov, A. Krokhin, M. Rolinek, in:, IEEE, 2015, pp. 1246–1258.
conference:
end_date: 2015-10-20
location: Berkeley, CA, United States
name: 'FOCS: Foundations of Computer Science'
start_date: 2015-10-18
date_created: 2018-12-11T11:53:10Z
date_published: 2015-12-01T00:00:00Z
date_updated: 2023-02-23T12:44:26Z
day: '01'
department:
- _id: VlKo
doi: 10.1109/FOCS.2015.80
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1502.07327
month: '12'
oa: 1
oa_version: Preprint
page: 1246 - 1258
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
publication_status: published
publisher: IEEE
publist_id: '5518'
quality_controlled: '1'
related_material:
record:
- id: '644'
relation: other
status: public
scopus_import: 1
status: public
title: The complexity of general-valued CSPs
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2015'
...
---
_id: '1675'
abstract:
- lang: eng
text: Proofs of work (PoW) have been suggested by Dwork and Naor (Crypto’92) as
protection to a shared resource. The basic idea is to ask the service requestor
to dedicate some non-trivial amount of computational work to every request. The
original applications included prevention of spam and protection against denial
of service attacks. More recently, PoWs have been used to prevent double spending
in the Bitcoin digital currency system. In this work, we put forward an alternative
concept for PoWs - so-called proofs of space (PoS), where a service requestor
must dedicate a significant amount of disk space as opposed to computation. We
construct secure PoS schemes in the random oracle model (with one additional mild
assumption required for the proof to go through), using graphs with high “pebbling
complexity” and Merkle hash-trees. We discuss some applications, including follow-up
work where a decentralized digital currency scheme called Spacecoin is constructed
that uses PoS (instead of wasteful PoW like in Bitcoin) to prevent double spending.
The main technical contribution of this work is the construction of (directed,
loop-free) graphs on N vertices with in-degree O(log logN) such that even if one
places Θ(N) pebbles on the nodes of the graph, there’s a constant fraction of
nodes that needs Θ(N) steps to be pebbled (where in every step one can put a pebble
on a node if all its parents have a pebble).
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Stefan
full_name: Dziembowski, Stefan
last_name: Dziembowski
- first_name: Sebastian
full_name: Faust, Sebastian
last_name: Faust
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
citation:
ama: 'Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. Proofs of space. In: 35th
Annual Cryptology Conference. Vol 9216. Springer; 2015:585-605. doi:10.1007/978-3-662-48000-7_29'
apa: 'Dziembowski, S., Faust, S., Kolmogorov, V., & Pietrzak, K. Z. (2015).
Proofs of space. In 35th Annual Cryptology Conference (Vol. 9216, pp. 585–605).
Santa Barbara, CA, United States: Springer. https://doi.org/10.1007/978-3-662-48000-7_29'
chicago: Dziembowski, Stefan, Sebastian Faust, Vladimir Kolmogorov, and Krzysztof
Z Pietrzak. “Proofs of Space.” In 35th Annual Cryptology Conference, 9216:585–605.
Springer, 2015. https://doi.org/10.1007/978-3-662-48000-7_29.
ieee: S. Dziembowski, S. Faust, V. Kolmogorov, and K. Z. Pietrzak, “Proofs of space,”
in 35th Annual Cryptology Conference, Santa Barbara, CA, United States,
2015, vol. 9216, pp. 585–605.
ista: 'Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. 2015. Proofs of space.
35th Annual Cryptology Conference. CRYPTO: International Cryptology Conference,
LNCS, vol. 9216, 585–605.'
mla: Dziembowski, Stefan, et al. “Proofs of Space.” 35th Annual Cryptology Conference,
vol. 9216, Springer, 2015, pp. 585–605, doi:10.1007/978-3-662-48000-7_29.
short: S. Dziembowski, S. Faust, V. Kolmogorov, K.Z. Pietrzak, in:, 35th Annual
Cryptology Conference, Springer, 2015, pp. 585–605.
conference:
end_date: 2015-08-20
location: Santa Barbara, CA, United States
name: 'CRYPTO: International Cryptology Conference'
start_date: 2015-08-16
date_created: 2018-12-11T11:53:24Z
date_published: 2015-08-01T00:00:00Z
date_updated: 2024-03-20T08:31:49Z
day: '01'
department:
- _id: VlKo
- _id: KrPi
doi: 10.1007/978-3-662-48000-7_29
ec_funded: 1
intvolume: ' 9216'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2013/796.pdf
month: '08'
oa: 1
oa_version: Preprint
page: 585 - 605
project:
- _id: 25FBA906-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '616160'
name: 'Discrete Optimization in Computer Vision: Theory and Practice'
- _id: 258C570E-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '259668'
name: Provable Security for Physical Cryptography
publication: 35th Annual Cryptology Conference
publication_identifier:
isbn:
- '9783662479995'
issn:
- 0302-9743
publication_status: published
publisher: Springer
publist_id: '5474'
pubrep_id: '671'
quality_controlled: '1'
related_material:
record:
- id: '2274'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Proofs of space
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 9216
year: '2015'
...
---
_id: '2275'
abstract:
- lang: eng
text: "Energies with high-order non-submodular interactions have been shown to be
very useful in vision due to their high modeling power. Optimization of such energies,
however, is generally NP-hard. A naive approach that works for small problem instances
is exhaustive search, that is, enumeration of all possible labelings of the underlying
graph. We propose a general minimization approach for large graphs based on enumeration
of labelings of certain small patches. \r\nThis partial enumeration technique
reduces complex high-order energy formulations to pairwise Constraint Satisfaction
Problems with unary costs (uCSP), which can be efficiently solved using standard
methods like TRW-S. Our approach outperforms a number of existing state-of-the-art
algorithms on well known difficult problems (e.g. curvature regularization, stereo,
deconvolution); it gives near global minimum and better speed. \r\nOur main application
of interest is curvature regularization. In the context of segmentation, our partial
enumeration technique allows to evaluate curvature directly on small patches using
a novel integral geometry approach.\r\n"
author:
- first_name: Carl
full_name: Olsson, Carl
last_name: Olsson
- first_name: Johannes
full_name: Ulen, Johannes
last_name: Ulen
- first_name: Yuri
full_name: Boykov, Yuri
last_name: Boykov
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Olsson C, Ulen J, Boykov Y, Kolmogorov V. Partial enumeration and curvature
regularization. In: IEEE; 2014:2936-2943. doi:10.1109/ICCV.2013.365'
apa: 'Olsson, C., Ulen, J., Boykov, Y., & Kolmogorov, V. (2014). Partial enumeration
and curvature regularization (pp. 2936–2943). Presented at the ICCV: International
Conference on Computer Vision, Sydney, Australia: IEEE. https://doi.org/10.1109/ICCV.2013.365'
chicago: Olsson, Carl, Johannes Ulen, Yuri Boykov, and Vladimir Kolmogorov. “Partial
Enumeration and Curvature Regularization,” 2936–43. IEEE, 2014. https://doi.org/10.1109/ICCV.2013.365.
ieee: 'C. Olsson, J. Ulen, Y. Boykov, and V. Kolmogorov, “Partial enumeration and
curvature regularization,” presented at the ICCV: International Conference on
Computer Vision, Sydney, Australia, 2014, pp. 2936–2943.'
ista: 'Olsson C, Ulen J, Boykov Y, Kolmogorov V. 2014. Partial enumeration and curvature
regularization. ICCV: International Conference on Computer Vision, 2936–2943.'
mla: Olsson, Carl, et al. Partial Enumeration and Curvature Regularization.
IEEE, 2014, pp. 2936–43, doi:10.1109/ICCV.2013.365.
short: C. Olsson, J. Ulen, Y. Boykov, V. Kolmogorov, in:, IEEE, 2014, pp. 2936–2943.
conference:
end_date: 2013-12-08
location: Sydney, Australia
name: 'ICCV: International Conference on Computer Vision'
start_date: 2013-12-01
date_created: 2018-12-11T11:56:42Z
date_published: 2014-03-03T00:00:00Z
date_updated: 2021-01-12T06:56:28Z
day: '03'
ddc:
- '000'
department:
- _id: VlKo
doi: 10.1109/ICCV.2013.365
file:
- access_level: open_access
checksum: 4a74b5c92d6dcd2348c2c10ec8dd18bf
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:09:30Z
date_updated: 2020-07-14T12:45:36Z
file_id: '4754'
file_name: IST-2016-566-v1+1_iccv13_part_enumeration.pdf
file_size: 378601
relation: main_file
file_date_updated: 2020-07-14T12:45:36Z
has_accepted_license: '1'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Submitted Version
page: 2936 - 2943
publication_status: published
publisher: IEEE
publist_id: '4669'
pubrep_id: '566'
quality_controlled: '1'
scopus_import: 1
status: public
title: Partial enumeration and curvature regularization
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2014'
...
---
_id: '7038'
article_processing_charge: No
author:
- first_name: Kristóf
full_name: Huszár, Kristóf
id: 33C26278-F248-11E8-B48F-1D18A9856A87
last_name: Huszár
orcid: 0000-0002-5445-5057
- first_name: Michal
full_name: Rolinek, Michal
id: 3CB3BC06-F248-11E8-B48F-1D18A9856A87
last_name: Rolinek
citation:
ama: Huszár K, Rolinek M. Playful Math - An Introduction to Mathematical Games.
IST Austria
apa: Huszár, K., & Rolinek, M. (n.d.). Playful Math - An introduction to
mathematical games. IST Austria.
chicago: Huszár, Kristóf, and Michal Rolinek. Playful Math - An Introduction
to Mathematical Games. IST Austria, n.d.
ieee: K. Huszár and M. Rolinek, Playful Math - An introduction to mathematical
games. IST Austria.
ista: Huszár K, Rolinek M. Playful Math - An introduction to mathematical games,
IST Austria, 5p.
mla: Huszár, Kristóf, and Michal Rolinek. Playful Math - An Introduction to Mathematical
Games. IST Austria.
short: K. Huszár, M. Rolinek, Playful Math - An Introduction to Mathematical Games,
IST Austria, n.d.
date_created: 2019-11-18T15:57:05Z
date_published: 2014-06-30T00:00:00Z
date_updated: 2020-07-14T23:11:45Z
day: '30'
ddc:
- '510'
department:
- _id: VlKo
- _id: UlWa
file:
- access_level: open_access
checksum: 2b94e5e1f4c3fe8ab89b12806276fb09
content_type: application/pdf
creator: dernst
date_created: 2019-11-18T15:57:51Z
date_updated: 2020-07-14T12:47:48Z
file_id: '7039'
file_name: 2014_Playful_Math_Huszar.pdf
file_size: 511233
relation: main_file
file_date_updated: 2020-07-14T12:47:48Z
has_accepted_license: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: '5'
publication_status: draft
publisher: IST Austria
status: public
title: Playful Math - An introduction to mathematical games
type: working_paper
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2014'
...
---
_id: '2270'
abstract:
- lang: eng
text: "Representation languages for coalitional games are a key research area in
algorithmic game theory. There is an inher-\r\nent tradeoff between how general
a language is, allowing it to capture more elaborate games, and how hard
\ it is computationally to optimize and solve such games. One prominent such
\ language is the simple yet expressive\r\nWeighted Graph Games (WGGs) representation
(Deng and Papadimitriou 1994), which maintains knowledge about synergies between
agents in the form of an edge weighted graph. We consider the problem of finding
\ the optimal coalition structure in WGGs. The agents in such games are vertices
in a graph, and the value of a coalition is the sum of the weights of the edges
present between coalition members. The optimal coalition structure is a partition
of the agents to coalitions, that maximizes the sum of utilities obtained by the
coalitions. We show that finding the optimal coalition structure is not
only hard for general graphs, but is also intractable for restricted families
such as planar graphs which are amenable for many other combinatorial problems.
\ We then provide algorithms with constant factor approximations for planar, minorfree
and bounded degree graphs."
author:
- first_name: Yoram
full_name: Bachrach, Yoram
last_name: Bachrach
- first_name: Pushmeet
full_name: Kohli, Pushmeet
last_name: Kohli
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Morteza
full_name: Zadimoghaddam, Morteza
last_name: Zadimoghaddam
citation:
ama: 'Bachrach Y, Kohli P, Kolmogorov V, Zadimoghaddam M. Optimal Coalition Structures
in Cooperative Graph Games. In: AAAI Press; 2013:81-87.'
apa: 'Bachrach, Y., Kohli, P., Kolmogorov, V., & Zadimoghaddam, M. (2013). Optimal
Coalition Structures in Cooperative Graph Games (pp. 81–87). Presented at the
AAAI: Conference on Artificial Intelligence, Bellevue, WA, United States: AAAI
Press.'
chicago: Bachrach, Yoram, Pushmeet Kohli, Vladimir Kolmogorov, and Morteza Zadimoghaddam.
“Optimal Coalition Structures in Cooperative Graph Games,” 81–87. AAAI Press,
2013.
ieee: 'Y. Bachrach, P. Kohli, V. Kolmogorov, and M. Zadimoghaddam, “Optimal Coalition
Structures in Cooperative Graph Games,” presented at the AAAI: Conference on Artificial
Intelligence, Bellevue, WA, United States, 2013, pp. 81–87.'
ista: 'Bachrach Y, Kohli P, Kolmogorov V, Zadimoghaddam M. 2013. Optimal Coalition
Structures in Cooperative Graph Games. AAAI: Conference on Artificial Intelligence,
81–87.'
mla: Bachrach, Yoram, et al. Optimal Coalition Structures in Cooperative Graph
Games. AAAI Press, 2013, pp. 81–87.
short: Y. Bachrach, P. Kohli, V. Kolmogorov, M. Zadimoghaddam, in:, AAAI Press,
2013, pp. 81–87.
conference:
end_date: 2013-07-18
location: Bellevue, WA, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2013-07-14
date_created: 2018-12-11T11:56:41Z
date_published: 2013-12-31T00:00:00Z
date_updated: 2021-01-12T06:56:25Z
day: '31'
department:
- _id: VlKo
external_id:
arxiv:
- '1108.5248'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1108.5248
month: '12'
oa: 1
oa_version: None
page: 81-87
publication_status: published
publisher: AAAI Press
publist_id: '4674'
quality_controlled: '1'
status: public
title: Optimal Coalition Structures in Cooperative Graph Games
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2013'
...
---
_id: '2273'
abstract:
- lang: eng
text: We propose a new family of message passing techniques for MAP estimation in
graphical models which we call Sequential Reweighted Message Passing (SRMP). Special
cases include well-known techniques such as Min-Sum Diusion (MSD) and a faster
Sequential Tree-Reweighted Message Passing (TRW-S). Importantly, our derivation
is simpler than the original derivation of TRW-S, and does not involve a decomposition
into trees. This allows easy generalizations. We present such a generalization
for the case of higher-order graphical models, and test it on several real-world
problems with promising results.
author:
- first_name: Vladimir
full_name: Vladimir Kolmogorov
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: Kolmogorov V. Reweighted Message Passing Revisited. IST Austria; 2013.
apa: Kolmogorov, V. (2013). Reweighted message passing revisited. IST Austria.
chicago: Kolmogorov, Vladimir. Reweighted Message Passing Revisited. IST
Austria, 2013.
ieee: V. Kolmogorov, Reweighted message passing revisited. IST Austria, 2013.
ista: Kolmogorov V. 2013. Reweighted message passing revisited, IST Austria,p.
mla: Kolmogorov, Vladimir. Reweighted Message Passing Revisited. IST Austria,
2013.
short: V. Kolmogorov, Reweighted Message Passing Revisited, IST Austria, 2013.
date_created: 2018-12-11T11:56:42Z
date_published: 2013-09-22T00:00:00Z
date_updated: 2019-01-24T13:07:32Z
day: '22'
department:
- _id: VlKo
extern: 0
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1309.5655
month: '09'
oa: 1
publication_status: published
publisher: IST Austria
publist_id: '4671'
quality_controlled: 0
status: public
title: Reweighted message passing revisited
type: report
year: '2013'
...
---
_id: '2276'
abstract:
- lang: eng
text: The problem of minimizing the Potts energy function frequently occurs in computer
vision applications. One way to tackle this NP-hard problem was proposed by Kovtun
[19, 20]. It identifies a part of an optimal solution by running k maxflow computations,
where k is the number of labels. The number of “labeled” pixels can be significant
in some applications, e.g. 50-93% in our tests for stereo. We show how to reduce
the runtime to O (log k) maxflow computations (or one parametric maxflow computation).
Furthermore, the output of our algorithm allows to speed-up the subsequent alpha
expansion for the unlabeled part, or can be used as it is for time-critical applications.
To derive our technique, we generalize the algorithm of Felzenszwalb et al. [7]
for Tree Metrics . We also show a connection to k-submodular functions from combinatorial
optimization, and discuss k-submodular relaxations for general energy functions.
author:
- first_name: Igor
full_name: Gridchyn, Igor
id: 4B60654C-F248-11E8-B48F-1D18A9856A87
last_name: Gridchyn
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Gridchyn I, Kolmogorov V. Potts model, parametric maxflow and k-submodular
functions. In: IEEE; 2013:2320-2327. doi:10.1109/ICCV.2013.288'
apa: 'Gridchyn, I., & Kolmogorov, V. (2013). Potts model, parametric maxflow
and k-submodular functions (pp. 2320–2327). Presented at the ICCV: International
Conference on Computer Vision, Sydney, Australia: IEEE. https://doi.org/10.1109/ICCV.2013.288'
chicago: Gridchyn, Igor, and Vladimir Kolmogorov. “Potts Model, Parametric Maxflow
and k-Submodular Functions,” 2320–27. IEEE, 2013. https://doi.org/10.1109/ICCV.2013.288.
ieee: 'I. Gridchyn and V. Kolmogorov, “Potts model, parametric maxflow and k-submodular
functions,” presented at the ICCV: International Conference on Computer Vision,
Sydney, Australia, 2013, pp. 2320–2327.'
ista: 'Gridchyn I, Kolmogorov V. 2013. Potts model, parametric maxflow and k-submodular
functions. ICCV: International Conference on Computer Vision, 2320–2327.'
mla: Gridchyn, Igor, and Vladimir Kolmogorov. Potts Model, Parametric Maxflow
and k-Submodular Functions. IEEE, 2013, pp. 2320–27, doi:10.1109/ICCV.2013.288.
short: I. Gridchyn, V. Kolmogorov, in:, IEEE, 2013, pp. 2320–2327.
conference:
end_date: 2013-12-08
location: Sydney, Australia
name: 'ICCV: International Conference on Computer Vision'
start_date: 2013-12-01
date_created: 2018-12-11T11:56:43Z
date_published: 2013-12-01T00:00:00Z
date_updated: 2021-01-12T06:56:28Z
day: '01'
department:
- _id: JoCs
- _id: VlKo
doi: 10.1109/ICCV.2013.288
external_id:
arxiv:
- '1310.1771'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1310.1771
month: '12'
oa: 1
oa_version: Preprint
page: 2320 - 2327
publication_status: published
publisher: IEEE
publist_id: '4668'
quality_controlled: '1'
status: public
title: Potts model, parametric maxflow and k-submodular functions
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2013'
...
---
_id: '2518'
abstract:
- lang: eng
text: A class of valued constraint satisfaction problems (VCSPs) is characterised
by a valued constraint language, a fixed set of cost functions on a finite domain.
An instance of the problem is specified by a sum of cost functions from the language
with the goal to minimise the sum. We study which classes of finite-valued languages
can be solved exactly by the basic linear programming relaxation (BLP). Thapper
and Živný showed [20] that if BLP solves the language then the language admits
a binary commutative fractional polymorphism. We prove that the converse is also
true. This leads to a necessary and a sufficient condition which can be checked
in polynomial time for a given language. In contrast, the previous necessary and
sufficient condition due to [20] involved infinitely many inequalities. More recently,
Thapper and Živný [21] showed (using, in particular, a technique introduced in
this paper) that core languages that do not satisfy our condition are NP-hard.
Taken together, these results imply that a finite-valued language can either be
solved using Linear Programming or is NP-hard.
alternative_title:
- LNCS
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Kolmogorov V. The power of linear programming for finite-valued CSPs: A constructive
characterization. In: Vol 7965. Springer; 2013:625-636. doi:10.1007/978-3-642-39206-1_53'
apa: 'Kolmogorov, V. (2013). The power of linear programming for finite-valued CSPs:
A constructive characterization (Vol. 7965, pp. 625–636). Presented at the ICALP:
Automata, Languages and Programming, Riga, Latvia: Springer. https://doi.org/10.1007/978-3-642-39206-1_53'
chicago: 'Kolmogorov, Vladimir. “The Power of Linear Programming for Finite-Valued
CSPs: A Constructive Characterization,” 7965:625–36. Springer, 2013. https://doi.org/10.1007/978-3-642-39206-1_53.'
ieee: 'V. Kolmogorov, “The power of linear programming for finite-valued CSPs: A
constructive characterization,” presented at the ICALP: Automata, Languages and
Programming, Riga, Latvia, 2013, vol. 7965, no. 1, pp. 625–636.'
ista: 'Kolmogorov V. 2013. The power of linear programming for finite-valued CSPs:
A constructive characterization. ICALP: Automata, Languages and Programming, LNCS,
vol. 7965, 625–636.'
mla: 'Kolmogorov, Vladimir. The Power of Linear Programming for Finite-Valued
CSPs: A Constructive Characterization. Vol. 7965, no. 1, Springer, 2013, pp.
625–36, doi:10.1007/978-3-642-39206-1_53.'
short: V. Kolmogorov, in:, Springer, 2013, pp. 625–636.
conference:
end_date: 2013-07-12
location: Riga, Latvia
name: 'ICALP: Automata, Languages and Programming'
start_date: 2013-07-08
date_created: 2018-12-11T11:58:08Z
date_published: 2013-07-01T00:00:00Z
date_updated: 2023-02-23T10:35:42Z
day: '01'
department:
- _id: VlKo
doi: 10.1007/978-3-642-39206-1_53
external_id:
arxiv:
- '1207.7213'
intvolume: ' 7965'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1207.7213
month: '07'
oa: 1
oa_version: Preprint
page: 625 - 636
publication_status: published
publisher: Springer
publist_id: '4383'
quality_controlled: '1'
related_material:
record:
- id: '2271'
relation: later_version
status: public
scopus_import: 1
status: public
title: 'The power of linear programming for finite-valued CSPs: A constructive characterization'
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 7965
year: '2013'
...
---
_id: '2828'
abstract:
- lang: eng
text: 'We study the complexity of valued constraint satisfaction problems (VCSPs)
parametrized by a constraint language, a fixed set of cost functions over a finite
domain. An instance of the problem is specified by a sum of cost functions from
the language and the goal is to minimize the sum. Under the unique games conjecture,
the approximability of finite-valued VCSPs is well understood, see Raghavendra
[2008]. However, there is no characterization of finite-valued VCSPs, let alone
general-valued VCSPs, that can be solved exactly in polynomial time, thus giving
insights from a combinatorial optimization perspective. We consider the case of
languages containing all possible unary cost functions. In the case of languages
consisting of only {0, ∞}-valued cost functions (i.e., relations), such languages
have been called conservative and studied by Bulatov [2003, 2011] and recently
by Barto [2011]. Since we study valued languages, we call a language conservative
if it contains all finite-valued unary cost functions. The computational complexity
of conservative valued languages has been studied by Cohen et al. [2006] for languages
over Boolean domains, by Deineko et al. [2008] for {0, 1}-valued languages (a.k.a
Max-CSP), and by Takhanov [2010a] for {0, ∞}-valued languages containing all finite-valued
unary cost functions (a.k.a. Min-Cost-Hom). We prove a Schaefer-like dichotomy
theorem for conservative valued languages: if all cost functions in the language
satisfy a certain condition (specified by a complementary combination of STP and
MJN multimor-phisms), then any instance can be solved in polynomial time (via
a new algorithm developed in this article), otherwise the language is NP-hard.
This is the first complete complexity classification of general-valued constraint
languages over non-Boolean domains. It is a common phenomenon that complexity
classifications of problems over non-Boolean domains are significantly harder
than the Boolean cases. The polynomial-time algorithm we present for the tractable
cases is a generalization of the submodular minimization problem and a result
of Cohen et al. [2008]. Our results generalize previous results by Takhanov [2010a]
and (a subset of results) by Cohen et al. [2006] and Deineko et al. [2008]. Moreover,
our results do not rely on any computer-assisted search as in Deineko et al. [2008],
and provide a powerful tool for proving hardness of finite-valued and general-valued
languages.'
article_number: '10'
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Stanislav
full_name: Živný, Stanislav
last_name: Živný
citation:
ama: Kolmogorov V, Živný S. The complexity of conservative valued CSPs. Journal
of the ACM. 2013;60(2). doi:10.1145/2450142.2450146
apa: Kolmogorov, V., & Živný, S. (2013). The complexity of conservative valued
CSPs. Journal of the ACM. ACM. https://doi.org/10.1145/2450142.2450146
chicago: Kolmogorov, Vladimir, and Stanislav Živný. “The Complexity of Conservative
Valued CSPs.” Journal of the ACM. ACM, 2013. https://doi.org/10.1145/2450142.2450146.
ieee: V. Kolmogorov and S. Živný, “The complexity of conservative valued CSPs,”
Journal of the ACM, vol. 60, no. 2. ACM, 2013.
ista: Kolmogorov V, Živný S. 2013. The complexity of conservative valued CSPs. Journal
of the ACM. 60(2), 10.
mla: Kolmogorov, Vladimir, and Stanislav Živný. “The Complexity of Conservative
Valued CSPs.” Journal of the ACM, vol. 60, no. 2, 10, ACM, 2013, doi:10.1145/2450142.2450146.
short: V. Kolmogorov, S. Živný, Journal of the ACM 60 (2013).
date_created: 2018-12-11T11:59:48Z
date_published: 2013-04-02T00:00:00Z
date_updated: 2021-01-12T07:00:00Z
day: '02'
department:
- _id: VlKo
doi: 10.1145/2450142.2450146
external_id:
arxiv:
- '1110.2809'
intvolume: ' 60'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1110.2809
month: '04'
oa: 1
oa_version: Preprint
publication: Journal of the ACM
publication_status: published
publisher: ACM
publist_id: '3971'
quality_controlled: '1'
scopus_import: 1
status: public
title: The complexity of conservative valued CSPs
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 60
year: '2013'
...
---
_id: '2901'
abstract:
- lang: eng
text: ' We introduce the M-modes problem for graphical models: predicting the M
label configurations of highest probability that are at the same time local maxima
of the probability landscape. M-modes have multiple possible applications: because
they are intrinsically diverse, they provide a principled alternative to non-maximum
suppression techniques for structured prediction, they can act as codebook vectors
for quantizing the configuration space, or they can form component centers for
mixture model approximation. We present two algorithms for solving the M-modes
problem. The first algorithm solves the problem in polynomial time when the underlying
graphical model is a simple chain. The second algorithm solves the problem for
junction chains. In synthetic and real dataset, we demonstrate how M-modes can
improve the performance of prediction. We also use the generated modes as a tool
to understand the topography of the probability distribution of configurations,
for example with relation to the training set size and amount of noise in the
data. '
alternative_title:
- ' JMLR: W&CP'
author:
- first_name: Chao
full_name: Chen, Chao
id: 3E92416E-F248-11E8-B48F-1D18A9856A87
last_name: Chen
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Zhu
full_name: Yan, Zhu
last_name: Yan
- first_name: Dimitris
full_name: Metaxas, Dimitris
last_name: Metaxas
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Chen C, Kolmogorov V, Yan Z, Metaxas D, Lampert C. Computing the M most probable
modes of a graphical model. In: Vol 31. JMLR; 2013:161-169.'
apa: 'Chen, C., Kolmogorov, V., Yan, Z., Metaxas, D., & Lampert, C. (2013).
Computing the M most probable modes of a graphical model (Vol. 31, pp. 161–169).
Presented at the AISTATS: Conference on Uncertainty in Artificial Intelligence,
Scottsdale, AZ, United States: JMLR.'
chicago: Chen, Chao, Vladimir Kolmogorov, Zhu Yan, Dimitris Metaxas, and Christoph
Lampert. “Computing the M Most Probable Modes of a Graphical Model,” 31:161–69.
JMLR, 2013.
ieee: 'C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, and C. Lampert, “Computing the
M most probable modes of a graphical model,” presented at the AISTATS: Conference
on Uncertainty in Artificial Intelligence, Scottsdale, AZ, United States, 2013,
vol. 31, pp. 161–169.'
ista: 'Chen C, Kolmogorov V, Yan Z, Metaxas D, Lampert C. 2013. Computing the M
most probable modes of a graphical model. AISTATS: Conference on Uncertainty
in Artificial Intelligence, JMLR: W&CP, vol. 31, 161–169.'
mla: Chen, Chao, et al. Computing the M Most Probable Modes of a Graphical Model.
Vol. 31, JMLR, 2013, pp. 161–69.
short: C. Chen, V. Kolmogorov, Z. Yan, D. Metaxas, C. Lampert, in:, JMLR, 2013,
pp. 161–169.
conference:
end_date: 2013-05-01
location: Scottsdale, AZ, United States
name: ' AISTATS: Conference on Uncertainty in Artificial Intelligence'
start_date: 2013-04-29
date_created: 2018-12-11T12:00:14Z
date_published: 2013-01-01T00:00:00Z
date_updated: 2021-01-12T07:00:35Z
day: '01'
department:
- _id: HeEd
- _id: VlKo
- _id: ChLa
intvolume: ' 31'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://jmlr.org/proceedings/papers/v31/chen13a.html
month: '01'
oa: 1
oa_version: None
page: 161 - 169
publication_status: published
publisher: JMLR
publist_id: '3846'
quality_controlled: '1'
scopus_import: 1
status: public
title: Computing the M most probable modes of a graphical model
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 31
year: '2013'
...
---
_id: '2272'
abstract:
- lang: eng
text: "We consider Conditional Random Fields (CRFs) with pattern-based potentials
defined on a chain. In this model the energy of a string (labeling) x1...xn is
the sum of terms over intervals [i,j] where each term is non-zero only if the
substring xi...xj equals a prespecified pattern α. Such CRFs can be naturally
applied to many sequence tagging problems.\r\nWe present efficient algorithms
for the three standard inference tasks in a CRF, namely computing (i) the partition
function, (ii) marginals, and (iii) computing the MAP. Their complexities are
respectively O(nL), O(nLℓmax) and O(nLmin{|D|,log(ℓmax+1)}) where L is the combined
length of input patterns, ℓmax is the maximum length of a pattern, and D is the
input alphabet. This improves on the previous algorithms of (Ye et al., 2009)
whose complexities are respectively O(nL|D|), O(n|Γ|L2ℓ2max) and O(nL|D|), where
|Γ| is the number of input patterns.\r\nIn addition, we give an efficient algorithm
for sampling. Finally, we consider the case of non-positive weights. (Komodakis
& Paragios, 2009) gave an O(nL) algorithm for computing the MAP. We present
a modification that has the same worst-case complexity but can beat it in the
best case. "
alternative_title:
- JMLR
article_processing_charge: No
author:
- first_name: Rustem
full_name: Takhanov, Rustem
id: 2CCAC26C-F248-11E8-B48F-1D18A9856A87
last_name: Takhanov
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Takhanov R, Kolmogorov V. Inference algorithms for pattern-based CRFs on sequence
data. In: ICML’13 Proceedings of the 30th International Conference on International.
Vol 28. ML Research Press; 2013:145-153.'
apa: 'Takhanov, R., & Kolmogorov, V. (2013). Inference algorithms for pattern-based
CRFs on sequence data. In ICML’13 Proceedings of the 30th International Conference
on International (Vol. 28, pp. 145–153). Atlanta, GA, USA: ML Research Press.'
chicago: Takhanov, Rustem, and Vladimir Kolmogorov. “Inference Algorithms for Pattern-Based
CRFs on Sequence Data.” In ICML’13 Proceedings of the 30th International Conference
on International, 28:145–53. ML Research Press, 2013.
ieee: R. Takhanov and V. Kolmogorov, “Inference algorithms for pattern-based CRFs
on sequence data,” in ICML’13 Proceedings of the 30th International Conference
on International, Atlanta, GA, USA, 2013, vol. 28, no. 3, pp. 145–153.
ista: 'Takhanov R, Kolmogorov V. 2013. Inference algorithms for pattern-based CRFs
on sequence data. ICML’13 Proceedings of the 30th International Conference on
International. ICML: International Conference on Machine Learning, JMLR, vol.
28, 145–153.'
mla: Takhanov, Rustem, and Vladimir Kolmogorov. “Inference Algorithms for Pattern-Based
CRFs on Sequence Data.” ICML’13 Proceedings of the 30th International Conference
on International, vol. 28, no. 3, ML Research Press, 2013, pp. 145–53.
short: R. Takhanov, V. Kolmogorov, in:, ICML’13 Proceedings of the 30th International
Conference on International, ML Research Press, 2013, pp. 145–153.
conference:
end_date: 2013-06-21
location: Atlanta, GA, USA
name: 'ICML: International Conference on Machine Learning'
start_date: 2013-06-16
date_created: 2018-12-11T11:56:41Z
date_published: 2013-06-01T00:00:00Z
date_updated: 2023-10-17T09:51:32Z
day: '01'
department:
- _id: VlKo
intvolume: ' 28'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://proceedings.mlr.press/v28/takhanov13.pdf?CFID=105472548&CFTOKEN=5c5859b5d97b4439-27B4AC58-BA92-A964-B598CAACEE6CC515
month: '06'
oa: 1
oa_version: Submitted Version
page: 145 - 153
publication: ICML'13 Proceedings of the 30th International Conference on International
publication_status: published
publisher: ML Research Press
publist_id: '4672'
quality_controlled: '1'
related_material:
record:
- id: '1794'
relation: later_version
status: public
scopus_import: '1'
status: public
title: Inference algorithms for pattern-based CRFs on sequence data
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 28
year: '2013'
...
---
_id: '2274'
abstract:
- lang: eng
text: "Proofs of work (PoW) have been suggested by Dwork and Naor (Crypto'92) as
protection to a shared resource. The basic idea is to ask the service requestor
to dedicate some non-trivial amount of computational work to every request. The
original applications included prevention of spam and protection against denial
of service attacks. More recently, PoWs have been used to prevent double spending
in the Bitcoin digital currency system.\r\n\r\nIn this work, we put forward an
alternative concept for PoWs -- so-called proofs of space (PoS), where a service
requestor must dedicate a significant amount of disk space as opposed to computation.
We construct secure PoS schemes in the random oracle model, using graphs with
high "pebbling complexity" and Merkle hash-trees. "
author:
- first_name: Stefan
full_name: Dziembowski, Stefan
last_name: Dziembowski
- first_name: Sebastian
full_name: Faust, Sebastian
last_name: Faust
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
citation:
ama: Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. Proofs of Space.
IST Austria; 2013.
apa: Dziembowski, S., Faust, S., Kolmogorov, V., & Pietrzak, K. Z. (2013). Proofs
of Space. IST Austria.
chicago: Dziembowski, Stefan, Sebastian Faust, Vladimir Kolmogorov, and Krzysztof
Z Pietrzak. Proofs of Space. IST Austria, 2013.
ieee: S. Dziembowski, S. Faust, V. Kolmogorov, and K. Z. Pietrzak, Proofs of
Space. IST Austria, 2013.
ista: Dziembowski S, Faust S, Kolmogorov V, Pietrzak KZ. 2013. Proofs of Space,
IST Austria,p.
mla: Dziembowski, Stefan, et al. Proofs of Space. IST Austria, 2013.
short: S. Dziembowski, S. Faust, V. Kolmogorov, K.Z. Pietrzak, Proofs of Space,
IST Austria, 2013.
date_created: 2018-12-11T11:56:42Z
date_published: 2013-11-28T00:00:00Z
date_updated: 2024-03-20T08:31:49Z
day: '28'
ddc:
- '530'
department:
- _id: VlKo
- _id: KrPi
file:
- access_level: open_access
checksum: 37b61637b62fc079d9141c59d9f1a94f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:11Z
date_updated: 2020-07-14T12:45:36Z
file_id: '5197'
file_name: IST-2016-671-v1+1_796.pdf
file_size: 405870
relation: main_file
file_date_updated: 2020-07-14T12:45:36Z
has_accepted_license: '1'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
publication_status: published
publisher: IST Austria
publist_id: '4670'
pubrep_id: '671'
related_material:
record:
- id: '1675'
relation: later_version
status: public
scopus_import: 1
status: public
title: Proofs of Space
type: report
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2013'
...
---
_id: '2930'
abstract:
- lang: eng
text: "In this paper we investigate k-submodular functions. This natural family
of discrete functions includes submodular and bisubmodular functions as the special
cases k = 1 and k = 2 respectively.\r\n\r\nIn particular we generalize the known
Min-Max-Theorem for submodular and bisubmodular functions. This theorem asserts
that the minimum of the (bi)submodular function can be found by solving a maximization
problem over a (bi)submodular polyhedron. We define a k-submodular polyhedron,
prove a Min-Max-Theorem for k-submodular functions, and give a greedy algorithm
to construct the vertices of the polyhedron.\r\n"
acknowledgement: "We would like to thank Andrei Krokhin for encourag- ing our cooperation,
for helpful discussions, and for his critical reading of the manuscript.\r\n"
alternative_title:
- LNCS
author:
- first_name: Anna
full_name: Huber, Anna
last_name: Huber
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: 'Huber A, Kolmogorov V. Towards minimizing k-submodular functions. In: Vol
7422. Springer; 2012:451-462. doi:10.1007/978-3-642-32147-4_40'
apa: 'Huber, A., & Kolmogorov, V. (2012). Towards minimizing k-submodular functions
(Vol. 7422, pp. 451–462). Presented at the ISCO: International Symposium on Combinatorial
Optimization, Athens, Greece: Springer. https://doi.org/10.1007/978-3-642-32147-4_40'
chicago: Huber, Anna, and Vladimir Kolmogorov. “Towards Minimizing K-Submodular
Functions,” 7422:451–62. Springer, 2012. https://doi.org/10.1007/978-3-642-32147-4_40.
ieee: 'A. Huber and V. Kolmogorov, “Towards minimizing k-submodular functions,”
presented at the ISCO: International Symposium on Combinatorial Optimization,
Athens, Greece, 2012, vol. 7422, pp. 451–462.'
ista: 'Huber A, Kolmogorov V. 2012. Towards minimizing k-submodular functions. ISCO:
International Symposium on Combinatorial Optimization, LNCS, vol. 7422, 451–462.'
mla: Huber, Anna, and Vladimir Kolmogorov. Towards Minimizing K-Submodular Functions.
Vol. 7422, Springer, 2012, pp. 451–62, doi:10.1007/978-3-642-32147-4_40.
short: A. Huber, V. Kolmogorov, in:, Springer, 2012, pp. 451–462.
conference:
end_date: 2012-04-21
location: Athens, Greece
name: 'ISCO: International Symposium on Combinatorial Optimization'
start_date: 2012-04-19
date_created: 2018-12-11T12:00:24Z
date_published: 2012-04-01T00:00:00Z
date_updated: 2021-01-12T07:00:46Z
day: '01'
department:
- _id: VlKo
doi: 10.1007/978-3-642-32147-4_40
intvolume: ' 7422'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1309.5469
month: '04'
oa: 1
oa_version: Preprint
page: 451 - 462
publication_status: published
publisher: Springer
publist_id: '3806'
quality_controlled: '1'
scopus_import: 1
status: public
title: Towards minimizing k-submodular functions
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 7422
year: '2012'
...
---
_id: '2928'
abstract:
- lang: eng
text: ' This paper addresses the problem of approximate MAP-MRF inference in
general graphical models. Following [36], we consider a family of linear programming
relaxations of the problem where each relaxation is specified by a set of nested
pairs of factors for which the marginalization constraint needs to be enforced.
We develop a generalization of the TRW-S algorithm [9] for this problem, where
we use a decomposition into junction chains, monotonic w.r.t. some ordering on
the nodes. This generalizes the monotonic chains in [9] in a natural way. We also
show how to deal with nested factors in an efficient way. Experiments show an
improvement over min-sum diffusion, MPLP and subgradient ascent algorithms on
a number of computer vision and natural language processing problems. '
article_processing_charge: No
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Thomas
full_name: Schoenemann, Thomas
last_name: Schoenemann
citation:
ama: Kolmogorov V, Schoenemann T. Generalized sequential tree-reweighted message
passing. arXiv. 2012.
apa: Kolmogorov, V., & Schoenemann, T. (2012). Generalized sequential tree-reweighted
message passing. arXiv. ArXiv.
chicago: Kolmogorov, Vladimir, and Thomas Schoenemann. “Generalized Sequential Tree-Reweighted
Message Passing.” ArXiv. ArXiv, 2012.
ieee: V. Kolmogorov and T. Schoenemann, “Generalized sequential tree-reweighted
message passing,” arXiv. ArXiv, 2012.
ista: Kolmogorov V, Schoenemann T. 2012. Generalized sequential tree-reweighted
message passing. arXiv, .
mla: Kolmogorov, Vladimir, and Thomas Schoenemann. “Generalized Sequential Tree-Reweighted
Message Passing.” ArXiv, ArXiv, 2012.
short: V. Kolmogorov, T. Schoenemann, ArXiv (2012).
date_created: 2018-12-11T12:00:23Z
date_published: 2012-05-29T00:00:00Z
date_updated: 2021-01-12T07:00:45Z
day: '29'
department:
- _id: VlKo
external_id:
arxiv:
- '1205.6352'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1205.6352
month: '05'
oa: 1
oa_version: Preprint
page: '16'
publication: arXiv
publication_status: published
publisher: ArXiv
publist_id: '3809'
status: public
title: Generalized sequential tree-reweighted message passing
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2012'
...
---
_id: '2931'
abstract:
- lang: eng
text: "In this paper, we present a new approach for establishing correspondences
between sparse image features related by an unknown nonrigid mapping and corrupted
by clutter and occlusion, such as points extracted from images of different instances
of the same object category. We formulate this matching task as an energy minimization
problem by defining an elaborate objective function of the appearance and the
spatial arrangement of the features. Optimization of this energy is an instance
of graph matching, which is in general an NP-hard problem. We describe a novel
graph matching optimization technique, which we refer to as dual decomposition
(DD), and demonstrate on a variety of examples that this method outperforms existing
graph matching algorithms. In the majority of our examples, DD is able to find
the global minimum within a minute. The ability to globally optimize the objective
allows us to accurately learn the parameters of our matching model from training
examples. We show on several matching tasks that our learned model yields results
superior to those of state-of-the-art methods.\r\n"
acknowledgement: This research was funded in part by Microsoft Research.
author:
- first_name: Lorenzo
full_name: Torresani, Lorenzo
last_name: Torresani
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Carsten
full_name: Rother, Carsten
last_name: Rother
citation:
ama: Torresani L, Kolmogorov V, Rother C. A dual decomposition approach to feature
correspondence. IEEE Transactions on Pattern Analysis and Machine Intelligence.
2012;35(2):259-271. doi:10.1109/TPAMI.2012.105
apa: Torresani, L., Kolmogorov, V., & Rother, C. (2012). A dual decomposition
approach to feature correspondence. IEEE Transactions on Pattern Analysis and
Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2012.105
chicago: Torresani, Lorenzo, Vladimir Kolmogorov, and Carsten Rother. “A Dual Decomposition
Approach to Feature Correspondence.” IEEE Transactions on Pattern Analysis
and Machine Intelligence. IEEE, 2012. https://doi.org/10.1109/TPAMI.2012.105.
ieee: L. Torresani, V. Kolmogorov, and C. Rother, “A dual decomposition approach
to feature correspondence,” IEEE Transactions on Pattern Analysis and Machine
Intelligence, vol. 35, no. 2. IEEE, pp. 259–271, 2012.
ista: Torresani L, Kolmogorov V, Rother C. 2012. A dual decomposition approach to
feature correspondence. IEEE Transactions on Pattern Analysis and Machine Intelligence.
35(2), 259–271.
mla: Torresani, Lorenzo, et al. “A Dual Decomposition Approach to Feature Correspondence.”
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35,
no. 2, IEEE, 2012, pp. 259–71, doi:10.1109/TPAMI.2012.105.
short: L. Torresani, V. Kolmogorov, C. Rother, IEEE Transactions on Pattern Analysis
and Machine Intelligence 35 (2012) 259–271.
date_created: 2018-12-11T12:00:24Z
date_published: 2012-05-08T00:00:00Z
date_updated: 2021-01-12T07:00:46Z
day: '08'
department:
- _id: VlKo
doi: 10.1109/TPAMI.2012.105
intvolume: ' 35'
issue: '2'
language:
- iso: eng
month: '05'
oa_version: None
page: 259 - 271
project:
- _id: 2587B514-B435-11E9-9278-68D0E5697425
name: Microsoft Research Faculty Fellowship
publication: IEEE Transactions on Pattern Analysis and Machine Intelligence
publication_status: published
publisher: IEEE
publist_id: '3805'
quality_controlled: '1'
scopus_import: 1
status: public
title: A dual decomposition approach to feature correspondence
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2012'
...
---
_id: '3117'
abstract:
- lang: eng
text: We consider the problem of minimizing a function represented as a sum of submodular
terms. We assume each term allows an efficient computation of exchange capacities.
This holds, for example, for terms depending on a small number of variables, or
for certain cardinality-dependent terms. A naive application of submodular minimization
algorithms would not exploit the existence of specialized exchange capacity subroutines
for individual terms. To overcome this, we cast the problem as a submodular flow
(SF) problem in an auxiliary graph in such a way that applying most existing SF
algorithms would rely only on these subroutines. We then explore in more detail
Iwata's capacity scaling approach for submodular flows (Iwata 1997 [19]). In particular,
we show how to improve its complexity in the case when the function contains cardinality-dependent
terms.
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: Kolmogorov V. Minimizing a sum of submodular functions. Discrete Applied
Mathematics. 2012;160(15):2246-2258. doi:10.1016/j.dam.2012.05.025
apa: Kolmogorov, V. (2012). Minimizing a sum of submodular functions. Discrete
Applied Mathematics. Elsevier. https://doi.org/10.1016/j.dam.2012.05.025
chicago: Kolmogorov, Vladimir. “Minimizing a Sum of Submodular Functions.” Discrete
Applied Mathematics. Elsevier, 2012. https://doi.org/10.1016/j.dam.2012.05.025.
ieee: V. Kolmogorov, “Minimizing a sum of submodular functions,” Discrete Applied
Mathematics, vol. 160, no. 15. Elsevier, pp. 2246–2258, 2012.
ista: Kolmogorov V. 2012. Minimizing a sum of submodular functions. Discrete Applied
Mathematics. 160(15), 2246–2258.
mla: Kolmogorov, Vladimir. “Minimizing a Sum of Submodular Functions.” Discrete
Applied Mathematics, vol. 160, no. 15, Elsevier, 2012, pp. 2246–58, doi:10.1016/j.dam.2012.05.025.
short: V. Kolmogorov, Discrete Applied Mathematics 160 (2012) 2246–2258.
date_created: 2018-12-11T12:01:29Z
date_published: 2012-10-01T00:00:00Z
date_updated: 2021-01-12T07:41:11Z
day: '01'
department:
- _id: VlKo
doi: 10.1016/j.dam.2012.05.025
intvolume: ' 160'
issue: '15'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1006.1990
month: '10'
oa: 1
oa_version: Preprint
page: 2246 - 2258
publication: Discrete Applied Mathematics
publication_status: published
publisher: Elsevier
publist_id: '3582'
quality_controlled: '1'
scopus_import: 1
status: public
title: Minimizing a sum of submodular functions
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 160
year: '2012'
...
---
_id: '3257'
abstract:
- lang: eng
text: Consider a convex relaxation f̂ of a pseudo-Boolean function f. We say that
the relaxation is totally half-integral if f̂(x) is a polyhedral function with
half-integral extreme points x, and this property is preserved after adding an
arbitrary combination of constraints of the form x i=x j, x i=1-x j, and x i=γ
where γ∈{0,1,1/2} is a constant. A well-known example is the roof duality relaxation
for quadratic pseudo-Boolean functions f. We argue that total half-integrality
is a natural requirement for generalizations of roof duality to arbitrary pseudo-Boolean
functions. Our contributions are as follows. First, we provide a complete characterization
of totally half-integral relaxations f̂ by establishing a one-to-one correspondence
with bisubmodular functions. Second, we give a new characterization of bisubmodular
functions. Finally, we show some relationships between general totally half-integral
relaxations and relaxations based on the roof duality. On the conceptual level,
our results show that bisubmodular functions provide a natural generalization
of the roof duality approach to higher-order terms. This can be viewed as a non-submodular
analogue of the fact that submodular functions generalize the s-t minimum cut
problem with non-negative weights to higher-order terms.
author:
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
citation:
ama: Kolmogorov V. Generalized roof duality and bisubmodular functions. Discrete
Applied Mathematics. 2012;160(4-5):416-426. doi:10.1016/j.dam.2011.10.026
apa: Kolmogorov, V. (2012). Generalized roof duality and bisubmodular functions.
Discrete Applied Mathematics. Elsevier. https://doi.org/10.1016/j.dam.2011.10.026
chicago: Kolmogorov, Vladimir. “Generalized Roof Duality and Bisubmodular Functions.”
Discrete Applied Mathematics. Elsevier, 2012. https://doi.org/10.1016/j.dam.2011.10.026.
ieee: V. Kolmogorov, “Generalized roof duality and bisubmodular functions,” Discrete
Applied Mathematics, vol. 160, no. 4–5. Elsevier, pp. 416–426, 2012.
ista: Kolmogorov V. 2012. Generalized roof duality and bisubmodular functions. Discrete
Applied Mathematics. 160(4–5), 416–426.
mla: Kolmogorov, Vladimir. “Generalized Roof Duality and Bisubmodular Functions.”
Discrete Applied Mathematics, vol. 160, no. 4–5, Elsevier, 2012, pp. 416–26,
doi:10.1016/j.dam.2011.10.026.
short: V. Kolmogorov, Discrete Applied Mathematics 160 (2012) 416–426.
date_created: 2018-12-11T12:02:18Z
date_published: 2012-03-01T00:00:00Z
date_updated: 2023-02-23T11:04:49Z
day: '01'
department:
- _id: VlKo
doi: 10.1016/j.dam.2011.10.026
external_id:
arxiv:
- '1005.2305'
intvolume: ' 160'
issue: 4-5
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1005.2305
month: '03'
oa: 1
oa_version: Preprint
page: 416 - 426
publication: Discrete Applied Mathematics
publication_status: published
publisher: Elsevier
publist_id: '3397'
quality_controlled: '1'
related_material:
record:
- id: '2934'
relation: earlier_version
status: public
scopus_import: 1
status: public
title: Generalized roof duality and bisubmodular functions
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 160
year: '2012'
...
---
_id: '3124'
abstract:
- lang: eng
text: "We consider the problem of inference in a graphical model with binary variables.
While in theory it is arguably preferable to compute marginal probabilities, in
practice researchers often use MAP inference due to the availability of efficient
discrete optimization algorithms. We bridge the gap between the two approaches
by introducing the Discrete Marginals technique in which approximate marginals
are obtained by minimizing an objective function with unary and pairwise terms
over a discretized domain. This allows the use of techniques originally developed
for MAP-MRF inference and learning. We explore two ways to set up the objective
function - by discretizing the Bethe free energy and by learning it from training
data. Experimental results show that for certain types of graphs a learned function
can outperform the Bethe approximation. We also establish a link between the Bethe
free energy and submodular functions.\r\n"
alternative_title:
- Inferning 2012
author:
- first_name: Filip
full_name: Korc, Filip
id: 476A2FD6-F248-11E8-B48F-1D18A9856A87
last_name: Korc
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Korc F, Kolmogorov V, Lampert C. Approximating marginals using discrete energy
minimization. In: ICML; 2012.'
apa: 'Korc, F., Kolmogorov, V., & Lampert, C. (2012). Approximating marginals
using discrete energy minimization. Presented at the ICML: International Conference
on Machine Learning, Edinburgh, Scotland: ICML.'
chicago: Korc, Filip, Vladimir Kolmogorov, and Christoph Lampert. “Approximating
Marginals Using Discrete Energy Minimization.” ICML, 2012.
ieee: 'F. Korc, V. Kolmogorov, and C. Lampert, “Approximating marginals using discrete
energy minimization,” presented at the ICML: International Conference on Machine
Learning, Edinburgh, Scotland, 2012.'
ista: 'Korc F, Kolmogorov V, Lampert C. 2012. Approximating marginals using discrete
energy minimization. ICML: International Conference on Machine Learning, Inferning
2012, .'
mla: Korc, Filip, et al. Approximating Marginals Using Discrete Energy Minimization.
ICML, 2012.
short: F. Korc, V. Kolmogorov, C. Lampert, in:, ICML, 2012.
conference:
end_date: 2012-07-01
location: Edinburgh, Scotland
name: 'ICML: International Conference on Machine Learning'
start_date: 2012-06-26
date_created: 2018-12-11T12:01:31Z
date_published: 2012-06-30T00:00:00Z
date_updated: 2023-02-23T12:24:24Z
day: '30'
ddc:
- '000'
department:
- _id: ChLa
- _id: VlKo
file:
- access_level: open_access
checksum: 3d0d4246548c736857302aadb2ff5d15
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:11:34Z
date_updated: 2020-07-14T12:46:00Z
file_id: '4889'
file_name: IST-2016-565-v1+1_DM-inferning2012.pdf
file_size: 305836
relation: main_file
file_date_updated: 2020-07-14T12:46:00Z
has_accepted_license: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Submitted Version
publication_status: published
publisher: ICML
publist_id: '3575'
pubrep_id: '565'
quality_controlled: '1'
related_material:
record:
- id: '5396'
relation: later_version
status: public
status: public
title: Approximating marginals using discrete energy minimization
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2012'
...
---
_id: '5396'
abstract:
- lang: eng
text: We consider the problem of inference in agraphical model with binary variables.
While in theory it is arguably preferable to compute marginal probabilities, in
practice researchers often use MAP inference due to the availability of efficient
discrete optimization algorithms. We bridge the gap between the two approaches
by introducing the Discrete Marginals technique in which approximate marginals
are obtained by minimizing an objective function with unary and pair-wise terms
over a discretized domain. This allows the use of techniques originally devel-oped
for MAP-MRF inference and learning. We explore two ways to set up the objective
function - by discretizing the Bethe free energy and by learning it from training
data. Experimental results show that for certain types of graphs a learned function
can out-perform the Bethe approximation. We also establish a link between the
Bethe free energy and submodular functions.
alternative_title:
- IST Austria Technical Report
author:
- first_name: Filip
full_name: Korc, Filip
id: 476A2FD6-F248-11E8-B48F-1D18A9856A87
last_name: Korc
- first_name: Vladimir
full_name: Kolmogorov, Vladimir
id: 3D50B0BA-F248-11E8-B48F-1D18A9856A87
last_name: Kolmogorov
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: Korc F, Kolmogorov V, Lampert C. Approximating Marginals Using Discrete
Energy Minimization. IST Austria; 2012. doi:10.15479/AT:IST-2012-0003
apa: Korc, F., Kolmogorov, V., & Lampert, C. (2012). Approximating marginals
using discrete energy minimization. IST Austria. https://doi.org/10.15479/AT:IST-2012-0003
chicago: Korc, Filip, Vladimir Kolmogorov, and Christoph Lampert. Approximating
Marginals Using Discrete Energy Minimization. IST Austria, 2012. https://doi.org/10.15479/AT:IST-2012-0003.
ieee: F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete
energy minimization. IST Austria, 2012.
ista: Korc F, Kolmogorov V, Lampert C. 2012. Approximating marginals using discrete
energy minimization, IST Austria, 13p.
mla: Korc, Filip, et al. Approximating Marginals Using Discrete Energy Minimization.
IST Austria, 2012, doi:10.15479/AT:IST-2012-0003.
short: F. Korc, V. Kolmogorov, C. Lampert, Approximating Marginals Using Discrete
Energy Minimization, IST Austria, 2012.
date_created: 2018-12-12T11:39:06Z
date_published: 2012-07-23T00:00:00Z
date_updated: 2023-02-23T11:13:22Z
day: '23'
ddc:
- '000'
department:
- _id: VlKo
- _id: ChLa
doi: 10.15479/AT:IST-2012-0003
file:
- access_level: open_access
checksum: 7e0ba85ad123b13223aaf6cdde2d288c
content_type: application/pdf
creator: system
date_created: 2018-12-12T11:53:29Z
date_updated: 2020-07-14T12:46:44Z
file_id: '5490'
file_name: IST-2012-0003_IST-2012-0003.pdf
file_size: 618744
relation: main_file
file_date_updated: 2020-07-14T12:46:44Z
has_accepted_license: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: '13'
publication_identifier:
issn:
- 2664-1690
publication_status: published
publisher: IST Austria
pubrep_id: '36'
related_material:
record:
- id: '3124'
relation: earlier_version
status: public
status: public
title: Approximating marginals using discrete energy minimization
type: technical_report
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2012'
...