Y. Shehu and O. S. Iyiola, “Weak convergence for variational inequalities with inertial-type method,” Applicable Analysis, vol. 101, no. 1. Taylor &; Francis, pp. 192–216, 2022.
LibreCat: https://research-explorer.ista.ac.at/record/7577
DOI: 10.1080/00036811.2020.1736287
WoS: 000518364100001
arXiv: 2101.08057

D. G. Harris, F. Iliopoulos, and V. Kolmogorov, “A new notion of commutativity for the algorithmic Lovász Local Lemma,” in Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, Virtual, 2021, vol. 207.
LibreCat: https://research-explorer.ista.ac.at/record/10072
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2021.31
arXiv: 2008.05569

V. Kolmogorov and T. Pock, “One-sided Frank-Wolfe algorithms for saddle problems,” in 38th International Conference on Machine Learning, Virtual, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/10552
arXiv: 2101.12617

M. Dvorak and S. Nicholson, “Massively winning configurations in the convex grabbing game on the plane,” in Proceedings of the 33rd Canadian Conference on Computational Geometry, Halifax, NS, Canada.
LibreCat: https://research-explorer.ista.ac.at/record/9592
arXiv: 2106.11247

O. S. Iyiola, C. D. Enyi, and Y. Shehu, “Reflected three-operator splitting method for monotone inclusion problem,” Optimization Methods and Software. Taylor and Francis, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9469
DOI: 10.1080/10556788.2021.1924715
WoS: 000650507600001

C. Izuchukwu and Y. Shehu, “New inertial projection methods for solving multivalued variational inequality problems beyond monotonicity,” Networks and Spatial Economics, vol. 21, no. 2. Springer Nature, pp. 291–323, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9234
DOI: 10.1007/s11067-021-09517-w
WoS: 000625002100001

A. Bloch-Hansen, N. Samei, and R. Solis-Oba, “Experimental evaluation of a local search approximation algorithm for the multiway cut problem,” in Conference on Algorithms and Discrete Applied Mathematics, Rupnagar, India, 2021, vol. 12601, pp. 346–358.
LibreCat: https://research-explorer.ista.ac.at/record/9227
DOI: 10.1007/978-3-030-67899-9_28

Y. Shehu, O. S. Iyiola, D. V. Thong, and N. T. C. Van, “An inertial subgradient extragradient algorithm extended to pseudomonotone equilibrium problems,” Mathematical Methods of Operations Research, vol. 93, no. 2. Springer Nature, pp. 213–242, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/8817
DOI: 10.1007/s00186-020-00730-w
WoS: 000590497300001

O. S. Iyiola and Y. Shehu, “New convergence results for inertial Krasnoselskii–Mann iterations in Hilbert spaces with applications,” Results in Mathematics, vol. 76, no. 2. Springer Nature, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9315
DOI: 10.1007/s00025-021-01381-x
WoS: 000632917700001

F. U. Ogbuisi, Y. Shehu, and J. C. Yao, “Convergence analysis of new inertial method for the split common null point problem,” Optimization. Taylor and Francis, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9365
DOI: 10.1080/02331934.2021.1914035
WoS: 000640109300001

Y. Shehu, Q.-L. Dong, L.-L. Liu, and J.-C. Yao, “New strong convergence method for the sum of two maximal monotone operators,” Optimization and Engineering, vol. 22. Springer Nature, pp. 2627–2653, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/8196
DOI: 10.1007/s11081-020-09544-5
WoS: 000559345400001

Y. Shehu and A. Gibali, “New inertial relaxed method for solving split feasibilities,” Optimization Letters, vol. 15. Springer Nature, pp. 2109–2126, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/7925
DOI: 10.1007/s11590-020-01603-1
WoS: 000537342300001

Y. Shehu, X.-H. Li, and Q.-L. Dong, “An efficient projection-type method for monotone variational inequalities in Hilbert spaces,” Numerical Algorithms, vol. 84. Springer Nature, pp. 365–388, 2020.
LibreCat: https://research-explorer.ista.ac.at/record/6593
DOI: 10.1007/s11075-019-00758-y
WoS: 000528979000015

Y. Shehu and O. S. Iyiola, “Projection methods with alternating inertial steps for variational inequalities: Weak and linear convergence,” Applied Numerical Mathematics, vol. 157. Elsevier, pp. 315–337, 2020.
LibreCat: https://research-explorer.ista.ac.at/record/8077
DOI: 10.1016/j.apnum.2020.06.009
WoS: 000564648400018

Y. Shehu, A. Gibali, and S. Sagratella, “Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces,” Journal of Optimization Theory and Applications, vol. 184. Springer Nature, pp. 877–894, 2020.
LibreCat: https://research-explorer.ista.ac.at/record/7161
DOI: 10.1007/s10957-019-01616-6
WoS: 000511805200009

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.
LibreCat: https://research-explorer.ista.ac.at/record/6725
DOI: 10.4230/LIPICS.ICALP.2019.77
arXiv: 1803.02289

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.
LibreCat: https://research-explorer.ista.ac.at/record/6596
DOI: 10.1007/s00025-019-1061-4
WoS: 000473237500002
arXiv: 2101.09068

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.
LibreCat: https://research-explorer.ista.ac.at/record/7000
DOI: 10.1007/s40314-019-0955-9
WoS: 000488973100005
arXiv: 2101.09081

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.
LibreCat: https://research-explorer.ista.ac.at/record/7412
DOI: 10.1137/16m109332x
WoS: 000493900200005
arXiv: 1809.01537

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.
LibreCat: https://research-explorer.ista.ac.at/record/7468
DOI: 10.1109/CVPR.2019.01140
WoS: 000542649304076
arXiv: 1806.05049

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.
LibreCat: https://research-explorer.ista.ac.at/record/7639
DOI: 10.1109/ICCVW.2019.00097
WoS: 000554591600090

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.
LibreCat: https://research-explorer.ista.ac.at/record/703
DOI: 10.1109/TPAMI.2017.2730884
arXiv: 1508.07902

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.
LibreCat: https://research-explorer.ista.ac.at/record/10864
DOI: 10.1007/978-3-319-74772-9_7
arXiv: 1502.01072

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.
LibreCat: https://research-explorer.ista.ac.at/record/273
DOI: 10.1109/cvpr.2018.00389
WoS: 000457843603087
arXiv: 1604.08269

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.
LibreCat: https://research-explorer.ista.ac.at/record/193
DOI: 10.1145/3196494.3196534
WoS: 000516620100005

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.
LibreCat: https://research-explorer.ista.ac.at/record/5975
DOI: 10.1137/16m1093306
WoS: 000453785100001
arXiv: 1506.08547

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.
LibreCat: https://research-explorer.ista.ac.at/record/5978
WoS: 000485488906082
arXiv: 2004.06370

V. Kolmogorov and M. Rolinek, “Superconcentrators of density 25.3,” Ars Combinatoria, vol. 141, no. 10. Charles Babbage Research Centre, pp. 269–304, 2018.
LibreCat: https://research-explorer.ista.ac.at/record/18
WoS: 000446809500022
arXiv: 1405.7828

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.
LibreCat: https://research-explorer.ista.ac.at/record/6032
DOI: 10.1145/3230649
WoS: 000468036500007
arXiv: 1602.03124

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.
LibreCat: https://research-explorer.ista.ac.at/record/5573
DOI: 10.15479/AT:ISTA:82

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.
LibreCat: https://research-explorer.ista.ac.at/record/641
DOI: 10.1007/978-3-319-58771-4_26

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.
LibreCat: https://research-explorer.ista.ac.at/record/644
DOI: 10.1137/16M1091836

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.
LibreCat: https://research-explorer.ista.ac.at/record/646
DOI: 10.1007/978-3-319-58771-4_19

M. Rolinek, “Complexity of constraint satisfaction,” Institute of Science and Technology Austria, 2017.
LibreCat: https://research-explorer.ista.ac.at/record/992
DOI: 10.15479/AT:ISTA:th_815

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.
LibreCat: https://research-explorer.ista.ac.at/record/1192
DOI: 10.1137/1.9781611974782.20
WoS: 000426965800020

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.
LibreCat: https://research-explorer.ista.ac.at/record/916
DOI: 10.1109/CVPR.2017.747
WoS: 000418371407018

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.
LibreCat: https://research-explorer.ista.ac.at/record/915
DOI: 10.1109/CVPR.2017.530
WoS: 000418371405009

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.
LibreCat: https://research-explorer.ista.ac.at/record/917
DOI: 10.1109/CVPR.2017.526
WoS: 000418371405005

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.
LibreCat: https://research-explorer.ista.ac.at/record/274
arXiv: 1608.04223

D. Kainmueller, F. Jug, C. Rother, and G. Meyers, “Graph matching problems for annotating C. Elegans.” Institute of Science and Technology Austria, 2017.
LibreCat: https://research-explorer.ista.ac.at/record/5561
DOI: 10.15479/AT:ISTA:57

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.
LibreCat: https://research-explorer.ista.ac.at/record/1231
DOI: 10.1007/978-3-662-49896-5_13

L. Barto and A. Kazda, “Deciding absorption,” International Journal of Algebra and Computation, vol. 26, no. 5. World Scientific Publishing, pp. 1033–1060, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/1353
DOI: 10.1142/S0218196716500430

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.
LibreCat: https://research-explorer.ista.ac.at/record/1377
DOI: 10.1137/15M1010257

A. Kazda, “CSP for binary conservative relational structures,” Algebra Universalis, vol. 75, no. 1. Springer, pp. 75–84, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/1612
DOI: 10.1007/s00012-015-0358-8

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.
LibreCat: https://research-explorer.ista.ac.at/record/1193
DOI: 10.1109/FOCS.2016.88
arXiv: 1506.08547

V. Kolmogorov and R. Takhanov, “Inference algorithms for pattern-based CRFs on sequence data,” Algorithmica, vol. 76, no. 1. Springer, pp. 17–46, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/1794
DOI: 10.1007/s00453-015-0017-7
arXiv: 1210.0508

P. Swoboda, “Synthetic discrete tomography problems.” Institute of Science and Technology Austria, 2016.
LibreCat: https://research-explorer.ista.ac.at/record/5557
DOI: 10.15479/AT:ISTA:46

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.
LibreCat: https://research-explorer.ista.ac.at/record/1636
DOI: 10.1007/978-3-662-48971-0_48
arXiv: 1504.07067

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.
LibreCat: https://research-explorer.ista.ac.at/record/1841
DOI: 10.1109/TPAMI.2014.2363465

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.
LibreCat: https://research-explorer.ista.ac.at/record/1859
DOI: 10.1109/CVPR.2015.7298890