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 

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 

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 

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 

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 

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 

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 

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 

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 

Alwen, J. F., Gazi, P., Kamath Hosdurg, C., Klein, K., Osang, G. F., Pietrzak, K. Z.,https://doi.org/10.1145/3196494.3196534__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