Publications

Kroshnin, A., Dvinskikh, D., Dvurechensky, P., Gasnikov, A., Tupitsa, N., Uribe, C.A. On the complexity of approximating wasserstein barycenters (2019) 36th International Conference on Machine Learning, ICML 2019, 2019-June, pp. 6176-6208. Scopus DOI

Bayandina, A.S., Gasnikov, A.V., Gasnikova, E.V., Matsievskii, S.V. Primal–Dual Mirror Descent Method for Constraint Stochastic Optimization Problems (2018) Computational Mathematics and Mathematical Physics, 58 (11), pp. 1728-1736. Scopus DOI Q2

Gasnikov, A.V., Gasnikova, E.V., Nesterov, Y.E. Dual Methods for Finding Equilibriums in Mixed Models of Flow Distribution in Large Transportation Networks (2018) Computational Mathematics and Mathematical Physics, 58 (9), pp. 1395-1403. Scopus DOI Q2

Gasnikov, A.V., Nesterov, Y.E. Universal Method for Stochastic Composite Optimization Problems (2018) Computational Mathematics and Mathematical Physics, 58 (1), pp. 48-64. Scopus DOI Q2

Bayandina, A.S., Gasnikov, A.V., Lagunovskaya, A.A. Gradient-Free Two-Point Methods for Solving Stochastic Nonsmooth Convex Optimization Problems with Small Non-Random Noises (2018) Automation and Remote Control, 79 (8), pp. 1399-1408. Scopus DOI Q3

Gasnikov, A.V., Gorbunov, E.A., Kovalev, D.A., Mohammed, A.A.M., Chernousova, E.O. The global rate of convergence for optimal tensor methods in smooth convex optimization [Обоснование гипотезы об оптимальных оценках скорости сходимости численных методов выпуклой оптимизации высоких порядков] (2018) Computer Research and Modeling, 10 (6), pp. 737-753. Scopus DOI Q4

Bayandina, A., Dvurechensky, P., Gasnikov, A., Stonyakin, F., Titov, A. Mirror descent and convex optimization problems with non-smooth inequality constraints (2018) Lecture Notes in Mathematics, 2227, pp. 181-213. Scopus DOI Q4

Gasnikov, A.V., Kubentayeva, M.B. Searching stochastic equilibria in transport networks by universal primal-dual gradient method (2018) Computer Research and Modeling, 10 (3), pp. 335-345. Scopus DOI Q4

Gasnikov, A.V., Kovalev, D.A. A hypothesis about the rate of global convergence for optimal methods (Newton's type) in smooth convex optimization (2018) Computer Research and Modeling, 10 (3), pp. 305-314. Scopus DOI Q4

Dvurechensky, P.E., Gasnikov, A.V., Lagunovskaya, A.A. Parallel Algorithms and Probability of Large Deviation for Stochastic Convex Optimization Problems (2018) Numerical Analysis and Applications, 11 (1), pp. 33-37. Scopus DOI Q4

Gasnikov, A.V., Dvurechensky, P.E., Zhukovskii, M.E., Kim, S.V., Plaunov, S.S., Smirnov, D.A., Noskov, F.A. About the Power Law of the PageRank Vector Component Distribution. Part 2. The Buckley–Osthus Model, Verification of the Power Law for This Model, and Setup of Real Search Engines (2018) Numerical Analysis and Applications, 11 (1), pp. 16-32. Scopus DOI Q4

Uribe, C.A., Dvinskikh, D., Dvurechensky, P., Gasnikov, A., Nedic, A. Distributed Computation of Wasserstein Barycenters over Networks (2018) Proceedings of the IEEE Conference on Decision and Control, 2018-December, статья № 8619160, pp. 6544-6549. Scopus DOI

Dvurechensky, P., Dvinskikh, D., Gasnikov, A., Uribe, C.A., Nedić, A. Decentralize and randomize: Faster algorithm for Wasserstein barycenters (2018) Advances in Neural Information Processing Systems, 2018-December, pp. 10760-10770. Scopus DOI

Dvurechensky, P., Gasnikov, A., Kroshnin, A. Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm (2018) 35th International Conference on Machine Learning, ICML 2018, 3, pp. 2196-2220. Scopus DOI

Anikin, A.S., Gasnikov, A.V., Dvurechensky, P.E., Tyurin, A.I., Chernov, A.V. Dual approaches to the minimization of strongly convex functionals with a simple structure under affine constraints (2017) Computational Mathematics and Mathematical Physics, 57 (8), pp. 1262-1276. Scopus DOI Q2