Computational optimal transport: Complexity by accelerated gradient descent is better than by Sinkhorn’s algorithm P Dvurechensky, A Gasnikov, A Kroshnin
International conference on machine learning, 1367-1376, 2018
345 2018 Decentralize and randomize: Faster algorithm for Wasserstein barycenters P Dvurechenskii, D Dvinskikh, A Gasnikov, C Uribe, A Nedich
Advances in Neural Information Processing Systems 31, 2018
127 2018 On the complexity of approximating Wasserstein barycenters A Kroshnin, N Tupitsa, D Dvinskikh, P Dvurechensky, A Gasnikov, C Uribe
International conference on machine learning, 3530-3540, 2019
121 2019 Stochastic intermediate gradient method for convex problems with stochastic inexact oracle P Dvurechensky, A Gasnikov
Journal of Optimization Theory and Applications 171, 121-145, 2016
119 2016 On a combination of alternating minimization and Nesterov’s momentum S Guminov, P Dvurechensky, N Tupitsa, A Gasnikov
International conference on machine learning, 3886-3898, 2021
113 * 2021 Recent theoretical advances in non-convex optimization M Danilova, P Dvurechensky, A Gasnikov, E Gorbunov, S Guminov, ...
High-Dimensional Optimization and Probability: With a View Towards Data …, 2022
112 2022 Stochastic gradient methods with inexact oracle A Gasnikov, P Dvurechensky, Y Nesterov
arXiv preprint arXiv:1411.4218, 2014
108 * 2014 Near Optimal Methods for Minimizing Convex Functions with Lipschitz A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1392-1393, 2019
88 2019 Learning supervised pagerank with gradient-based and gradient-free optimization methods L Bogolubsky, P Dvurechenskii, A Gasnikov, G Gusev, Y Nesterov, ...
Advances in neural information processing systems 29, 2016
87 2016 Primal–dual accelerated gradient methods with small-dimensional relaxation oracle Y Nesterov, A Gasnikov, S Guminov, P Dvurechensky
Optimization Methods and Software 36 (4), 773-810, 2021
86 2021 Dual approaches to the minimization of strongly convex functionals with a simple structure under affine constraints AS Anikin, AV Gasnikov, PE Dvurechensky, AI Tyurin, AV Chernov
Computational Mathematics and Mathematical Physics 57, 1262-1276, 2017
80 * 2017 Optimal tensor methods in smooth convex and uniformly convexoptimization A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1374-1391, 2019
79 * 2019 Inexact model: A framework for optimization and variational inequalities F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ...
Optimization Methods and Software 36 (6), 1155-1201, 2021
74 * 2021 Mirror descent and convex optimization problems with non-smooth inequality constraints A Bayandina, P Dvurechensky, A Gasnikov, F Stonyakin, A Titov
Large-scale and distributed optimization, 181-213, 2018
71 2018 Fast primal-dual gradient method for strongly convex minimization problems with linear constraints A Chernov, P Dvurechensky, A Gasnikov
International conference on discrete optimization and operations research …, 2016
66 2016 Gradient methods for problems with inexact model of the objective FS Stonyakin, D Dvinskikh, P Dvurechensky, A Kroshnin, O Kuznetsova, ...
Mathematical Optimization Theory and Operations Research: 18th International …, 2019
63 2019 Distributed computation of Wasserstein barycenters over networks CA Uribe, D Dvinskikh, P Dvurechensky, A Gasnikov, A Nedić
2018 IEEE Conference on Decision and Control (CDC), 6544-6549, 2018
58 2018 High-probability bounds for stochastic optimization and variational inequalities: the case of unbounded variance A Sadiev, M Danilova, E Gorbunov, S Horváth, G Gidel, P Dvurechensky, ...
International Conference on Machine Learning, 29563-29648, 2023
54 2023 About accelerated randomized methods A Gasnikov, P Dvurechensky, I Usmanova
arXiv preprint arXiv:1508.02182, 2015
53 * 2015 An accelerated method for derivative-free smooth stochastic convex optimization E Gorbunov, P Dvurechensky, A Gasnikov
arXiv preprint arXiv:1802.09022, 2018
52 * 2018 
Alexander GasnikovMIPTOverená e-mailová adresa na: mipt.ru