Введение в математическое моделирование транспортных потоков А Гасников
Litres, 2022
582 * 2022 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
305 2018 A dual approach for optimal algorithms in distributed optimization over networks CA Uribe, S Lee, A Gasnikov, A Nedić
2020 Information Theory and Applications Workshop (ITA), 1-37, 2020
157 2020 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
120 2018 Современные численные методы оптимизации. Метод универсального градиентного спуска АВ Гасников
Федеральное государственное автономное образовательное учреждение высшего …, 2018
117 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
110 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
107 2016 Стохастические градиентные методы с неточным оракулом АВ Гасников, ПЕ Двуреченский, ЮЕ Нестеров
Труды Московского физико-технического института 8 (1 (29)), 41-91, 2016
105 * 2016 Stochastic optimization with heavy-tailed noise via accelerated gradient clipping E Gorbunov, M Danilova, A Gasnikov
Advances in Neural Information Processing Systems 33, 15042-15053, 2020
104 2020 Efficient numerical methods for entropy-linear programming problems AV Gasnikov, EB Gasnikova, YE Nesterov, AV Chernov
Computational Mathematics and Mathematical Physics 56, 514-524, 2016
85 * 2016 Near Optimal Methods for Minimizing Convex Functions with Lipschitz -th Derivatives A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1392-1393, 2019
80 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
74 2016 Universal method for stochastic composite optimization problems AV Gasnikov, YE Nesterov
Computational Mathematics and Mathematical Physics 58, 48-64, 2018
72 2018 Optimal decentralized distributed algorithms for stochastic convex optimization E Gorbunov, D Dvinskikh, A Gasnikov
arXiv preprint arXiv:1911.07363, 2019
71 2019 Decentralized and parallel primal and dual accelerated methods for stochastic convex programming problems D Dvinskikh, A Gasnikov
Journal of Inverse and Ill-posed Problems 29 (3), 385-405, 2021
69 2021 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
68 2021 Fast primal-dual gradient method for strongly convex minimization problems with linear constraints A Chernov, P Dvurechensky, A Gasnikov
Discrete Optimization and Operations Research: 9th International Conference …, 2016
67 2016 Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case AV Gasnikov, EA Krymova, AA Lagunovskaya, IN Usmanova, ...
Automation and remote control 78, 224-234, 2017
66 2017 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
65 2022 Optimal algorithms for distributed optimization CA Uribe, S Lee, A Gasnikov, A Nedić
arXiv preprint arXiv:1712.00232, 2017
62 2017