| 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 | 85 | 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 | 80 | 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 | 51 | 2018 |
| Optimal decentralized distributed algorithms for stochastic convex optimization E Gorbunov, D Dvinskikh, A Gasnikov arXiv preprint arXiv:1911.07363, 2019 | 50 | 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 | 49 | 2021 |
| Gradient methods for problems with inexact model of the objective FS Stonyakin, D Dvinskikh, P Dvurechensky, A Kroshnin, O Kuznetsova, ... International Conference on Mathematical Optimization Theory and Operations …, 2019 | 45 | 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 | 26 | 2019 |
| Inexact model: A framework for optimization and variational inequalities F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ... Optimization Methods and Software, 1-47, 2021 | 24 | 2021 |
| Decentralized distributed optimization for saddle point problems A Rogozin, A Beznosikov, D Dvinskikh, D Kovalev, P Dvurechensky, ... arXiv preprint arXiv:2102.07758, 2021 | 23 | 2021 |
| Inexact relative smoothness and strong convexity for optimization and variational inequalities by inexact model F Stonyakin, A Tyurin, A Gasnikov, P Dvurechensky, A Agafonov, ... arXiv preprint arXiv:2001.09013, 2020 | 23 | 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 | 19 | 2020 |
| Improved Complexity Bounds in Wasserstein Barycenter Problem D Dvinskikh, D Tiapkin arXiv preprint arXiv:2010.04677, 2020 | 18 | 2020 |
| Accelerated methods for composite non-bilinear saddle point problem M Alkousa, D Dvinskikh, F Stonyakin, A Gasnikov, D Kovalev arXiv preprint arXiv:1906.03620, 2019 | 17 | 2019 |
| Accelerated meta-algorithm for convex optimization problems AV Gasnikov, DM Dvinskikh, PE Dvurechensky, DI Kamzolov, ... Computational Mathematics and Mathematical Physics 61 (1), 17-28, 2021 | 15 | 2021 |
| Accelerated methods for saddle-point problem MS Alkousa, AV Gasnikov, DM Dvinskikh, DA Kovalev, FS Stonyakin Computational Mathematics and Mathematical Physics 60 (11), 1787-1809, 2020 | 15 | 2020 |
| Oracle complexity separation in convex optimization A Ivanova, P Dvurechensky, E Vorontsova, D Pasechnyuk, A Gasnikov, ... Journal of Optimization Theory and Applications 193 (1), 462-490, 2022 | 12 | 2022 |
| Adaptive gradient descent for convex and non-convex stochastic optimization D Dvinskikh, A Ogaltsov, A Gasnikov, P Dvurechensky, A Tyurin, ... arXiv preprint arXiv:1911.08380, 2019 | 11 | 2019 |
| Accelerated and Unaccelerated Stochastic Gradient Descent in Model Generality DM Dvinskikh, AI Tyurin, AV Gasnikov, CC Omel’chenko Mathematical Notes 108 (3), 511-522, 2020 | 8 | 2020 |
| On dual approach for distributed stochastic convex optimization over networks D Dvinskikh, E Gorbunov, A Gasnikov, P Dvurechensky, CA Uribe arXiv preprint arXiv:1903.09844, 2019 | 8 | 2019 |
| Decentralized algorithms for wasserstein barycenters D Dvinskikh PQDT-Global, 2021 | 6 | 2021 |
Alexander GasnikovMIPTVerified email at mipt.ru
