| Distributed learning with compressed gradient differences K Mishchenko, E Gorbunov, M Takáè, P Richtárik arXiv preprint arXiv:1901.09269, 2019 | 56 | 2019 |
| A unified theory of sgd: Variance reduction, sampling, quantization and coordinate descent E Gorbunov, F Hanzely, P Richtárik International Conference on Artificial Intelligence and Statistics, 680-690, 2020 | 42 | 2020 |
| An accelerated method for derivative-free smooth stochastic convex optimization E Gorbunov, P Dvurechensky, A Gasnikov arXiv preprint arXiv:1802.09022, 2018 | 42* | 2018 |
| The global rate of convergence for optimal tensor methods in smooth convex optimization A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ... arXiv preprint arXiv:1809.00382, 2018 | 33* | 2018 |
| Optimal decentralized distributed algorithms for stochastic convex optimization E Gorbunov, D Dvinskikh, A Gasnikov arXiv preprint arXiv:1911.07363, 2019 | 30 | 2019 |
| 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 | 26 | 2019 |
| On primal and dual approaches for distributed stochastic convex optimization over networks D Dvinskikh, E Gorbunov, A Gasnikov, P Dvurechensky, CA Uribe 2019 IEEE 58th Conference on Decision and Control (CDC), 7435-7440, 2019 | 20* | 2019 |
| Derivative-free method for composite optimization with applications to decentralized distributed optimization A Beznosikov, E Gorbunov, A Gasnikov IFAC-PapersOnLine 53 (2), 4038-4043, 2020 | 17* | 2020 |
| Accelerated directional search with non-Euclidean prox-structure EA Vorontsova, AV Gasnikov, EA Gorbunov Automation and Remote Control 80 (4), 693-707, 2019 | 16* | 2019 |
| An Accelerated Directional Derivative Method for Smooth Stochastic Convex Optimization EG Pavel Dvurechensky, Alexander Gasnikov arXiv preprint arXiv:1804.02394, 2018 | 15* | 2018 |
| Stochastic three points method for unconstrained smooth minimization EH Bergou, E Gorbunov, P Richtarik SIAM Journal on Optimization 30 (4), 2726-2749, 2020 | 12* | 2020 |
| Stochastic optimization with heavy-tailed noise via accelerated gradient clipping E Gorbunov, M Danilova, A Gasnikov Advances in Neural Information Processing Systems 33 (NeurIPS 2020) [arXiv …, 2020 | 11 | 2020 |
| Linearly Converging Error Compensated SGD E Gorbunov, D Kovalev, D Makarenko, P Richtárik Advances in Neural Information Processing Systems 33 (NeurIPS 2020) [arXiv …, 2020 | 9 | 2020 |
| A stochastic derivative free optimization method with momentum E Gorbunov, A Bibi, O Sener, EH Bergou, P Richtárik 8th International Conference on Learning Representations (ICLR 2020) [arXiv …, 2019 | 8 | 2019 |
| Stochastic spectral and conjugate descent methods D Kovalev, E Gorbunov, E Gasanov, P Richtárik arXiv preprint arXiv:1802.03703, 2018 | 7 | 2018 |
| Local sgd: Unified theory and new efficient methods E Gorbunov, F Hanzely, P Richtárik International Conference on Artificial Intelligence and Statistics, 3556-3564, 2021 | 6 | 2021 |
| Recent Theoretical Advances in Non-Convex Optimization M Danilova, P Dvurechensky, A Gasnikov, E Gorbunov, S Guminov, ... arXiv preprint arXiv:2012.06188, 2020 | 4 | 2020 |
| Recent theoretical advances in decentralized distributed convex optimization E Gorbunov, A Rogozin, A Beznosikov, D Dvinskikh, A Gasnikov arXiv preprint arXiv:2011.13259, 2020 | 4 | 2020 |
| Accelerated gradient-free optimization methods with a non-Euclidean proximal operator EA Vorontsova, AV Gasnikov, EA Gorbunov, PE Dvurechenskii Automation and Remote Control 80 (8), 1487-1501, 2019 | 3 | 2019 |
| On the Upper Bound for the Expectation of the Norm of a Vector Uniformly Distributed on the Sphere and the Phenomenon of Concentration of Uniform Measure on the Sphere. EA Gorbunov, EA Vorontsova, AV Gasnikov Mathematical Notes 106, 2019 | 3* | 2019 |
Alexander GasnikovMIPTVerified email at mipt.ru
