| Введение в математическое моделирование транспортных потоков А Гасников Litres, 2022 | 501* | 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 | 187 | 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 | 118 | 2020 |
| Стохастические градиентные методы с неточным оракулом АВ Гасников, ПЕ Двуреченский, ЮЕ Нестеров Труды Московского физико-технического института 8 (1 (29)), 41-91, 2016 | 95* | 2016 |
| Современные численные методы оптимизации. Метод универсального градиентного спуска АВ Гасников Федеральное государственное автономное образовательное учреждение высшего …, 2018 | 86 | 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 | 86 | 2018 |
| Stochastic intermediate gradient method for convex problems with stochastic inexact oracle P Dvurechensky, A Gasnikov Journal of Optimization Theory and Applications 171 (1), 121-145, 2016 | 84 | 2016 |
| 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 | 82 | 2019 |
| Об эффективных численных методах решения задач энтропийно-линейного программирования АВ Гасников, ЕВ Гасникова, ЮЕ Нестеров, АВ Чернов Журнал вычислительной математики и математической физики 56 (4), 523-534, 2016 | 70* | 2016 |
| 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 | 59 | 2016 |
| 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 | 59 | 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 | 54 | 2019 |
| Accelerated alternating minimization S Guminov, P Dvurechensky, A Gasnikov arXiv preprint arXiv:1906.03622, 2019 | 53* | 2019 |
| Universal method for stochastic composite optimization problems AV Gasnikov, YE Nesterov Computational Mathematics and Mathematical Physics 58 (1), 48-64, 2018 | 53 | 2018 |
| Optimal decentralized distributed algorithms for stochastic convex optimization E Gorbunov, D Dvinskikh, A Gasnikov arXiv preprint arXiv:1911.07363, 2019 | 52 | 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 | 51 | 2021 |
| 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 | 51 | 2018 |
| 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 | 51 | 2018 |
| О трехстадийной версии модели стационарной динамики транспортных потоков АВ Гасников, ЮВ Дорн, ЮЕ Нестеров, СВ Шпирко Математическое моделирование 26 (6), 34-70, 2014 | 51 | 2014 |
| 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 | 50 | 2021 |
Pavel DvurechenskyWeierstrass Institute for Applied Analysis and StochasticsVerified email at wias-berlin.de
