Pavel Dvurechensky
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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
Stochastic gradient methods with inexact oracle
A Gasnikov, P Dvurechensky, Y Nesterov
arXiv preprint arXiv:1411.4218, 2014
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
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
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
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 (8), 1262-1276, 2017
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
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 Researchá…, 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
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
Optimal tensor methods in smooth convex and uniformly convexoptimization
A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1374-1391, 2019
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
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
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
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
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 Operationsá…, 2019
Randomized similar triangles method: A unifying framework for accelerated randomized optimization methods (coordinate descent, directional search, derivative-free method)
P Dvurechensky, A Gasnikov, A Tiurin
arXiv preprint arXiv:1707.08486, 2017
About accelerated randomized methods
A Gasnikov, P Dvurechensky, I Usmanova
arXiv preprint arXiv:1508.02182, 2015
Численные методы поиска равновесного распределения потоков в модели Бэкмана и в модели стабильной динамики
АВ Гасников, ПЕ Двуреченский, ЮВ Дорн, ЮВ Максимов
Математическое моделирование 28 (10), 40-64, 2016
Efficient numerical algorithms for regularized regression problem with applications to traffic matrix estimations
A Anikin, P Dvurechensky, A Gasnikov, A Golov, A Gornov, Y Maximov, ...
arXiv preprint arXiv:1508.00858, 2015
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