V. Kolmogorov and R. Takhanov, “Inference algorithms for pattern-based CRFs on sequence data,” Algorithmica, vol. 76, no. 1. Springer, pp. 17–46, 2016.

P. Swoboda, “Synthetic discrete tomography problems.” Institute of Science and Technology Austria, 2016.

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.

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.

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.

V. Kolmogorov, J. Thapper, and S. divný, “The power of linear programming for general-valued CSPs,” SIAM Journal on Computing, vol. 44, no. 1. SIAM, pp. 1–36, 2015.

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.

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.

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.

K. Huszár and M. Rolinek, Playful Math - An introduction to mathematical games. IST Austria.

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.

V. Kolmogorov, Reweighted message passing revisited. IST Austria, 2013.

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.

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.

V. Kolmogorov and S. divný, “The complexity of conservative valued CSPs,” Journal of the ACM, vol. 60, no. 2. ACM, 2013.

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.

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.

S. Dziembowski, S. Faust, V. Kolmogorov, and K. Z. Pietrzak, Proofs of Space. IST Austria, 2013.

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.

V. Kolmogorov and T. Schoenemann, “Generalized sequential tree-reweighted message passing,” arXiv. ArXiv, 2012.

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.

V. Kolmogorov, “Minimizing a sum of submodular functions,” Discrete Applied Mathematics, vol. 160, no. 15. Elsevier, pp. 2246–2258, 2012.

V. Kolmogorov, “Generalized roof duality and bisubmodular functions,” Discrete Applied Mathematics, vol. 160, no. 4–5. Elsevier, pp. 416–426, 2012.

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.

F. Korc, V. Kolmogorov, and C. Lampert, Approximating marginals using discrete energy minimization. IST Austria, 2012.