Suivre
Pavel Dvurechensky
Titre
Citée par
Citée par
Année
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
3452018
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
1272018
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
1202019
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
1182016
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
108*2021
Stochastic gradient methods with inexact oracle
A Gasnikov, P Dvurechensky, Y Nesterov
arXiv preprint arXiv:1411.4218, 2014
108*2014
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
1072022
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
862019
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
832021
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
832016
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
78*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
682018
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
662016
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
612019
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
582018
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
51*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
502023
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