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20142026
most citedComputational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm

66 citations · 525 across the 94 of their papers we have counts for

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Showing 2015Show all

6 papers · 1 filter

math.PR2015

Stochastic Analysis in Problems, part 1 (in Russian)

Nazar Buzun, Alexander Gasnikov, Fedor Goncharov +5

This book contains a large number of exercises related to different stochastic disciplines. Difficulty of the problems varies from the basic level in the first chapter up to the an…

math.OC2015★ 7 cited

About accelerated randomized methods

Alexander Gasnikov, Pavel Dvurechensky, Ilnura Usmanova

We show how one can obtain nonaccelerated randomized coordinate descent method (Yu. Nesterov, 2010) and nonaccelerated method of randomization of sum-type functional (Le Roux-Schmi…

math.OC2015

Searching equillibriums in Beckmann's and Nesterov--de Palma's models

Alexander Gasnikov, Pavel Dvurechensky, Yuriy Dorn +1

In this paper we propose and develop classical Frank--Wolf algorithm for Beckmann's type models. This is not new, but we investigate details that allows us to speed up. We also con…

math.OC2015★ 7 cited

Universal method with inexact oracle and its applications for searching equillibriums in multistage transport problems

Alexander Gasnikov, Pavel Dvurechensky, Dmitry Kamzolov +5

In this paper we propose a new efficient approach for numerical calculation of equillibriums in multistage transport problems. In the very core of our approach lies the proper comb…

math.OC2015

Efficient calculation of stochastic equilibriums in the Beckmann's and stable dynamic models

Alexander Gasnikov, Evgenia Gasnikova, Pavel Dvurechensky +2

We propose composite approache to the special sum-type convex optimization problem with affine restriction and special entropy type regularization. Since the fuctional has a penalt…

math.OC2015★ 3 cited

Gradient and gradient-free methods for stochastic convex optimization with inexact oracle

Alexander Gasnikov, Pavel Dvurechensky, Dmitry Kamzolov

In the paper we generalize universal gradient method (Yu. Nesterov) to strongly convex case and to Intermediate gradient method (Devolder-Glineur-Nesterov). We also consider possib…