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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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math.OC2026

Lower Bounds For Gradient-Free Convex Optimization And Convex-Concave Saddle-Point Problems

Yuriy Dorn, Darina Dvinskikh, Timofei Loginov +4

We study the query complexity of optimization with exact scalar-value information. For globally -smooth convex functions on with a minimizer in a Euclidean ball of…

cs.LG2026

Clipped or Unclipped? Finite-Sample Trade-offs for Averaged SGD under Heavy-Tailed Noise

Alexandra Suvorikova, Egor Gladin, Darina Dvinskikh +5

Gradient clipping is widely used to stabilize training, but it need not improve the statistical accuracy of averaged SGD, even under heavy-tailed noise. We derive a finite-sample c…

math.OC2026

The Complexity of Convex Optimization with Mismatched Geometry

Timofei Loginov, Alexander Gasnikov, Yuriy Dorn +4

Optimal first-order methods on non-Euclidean domains such as the ball pair the prox-function with the norm in which smoothness…

math.OC2026

Certified Residual Quasi-Newton Methods for Distributed Variational Inequalities

Ewsey R. Obzherin, Roman M. Mozhaev, Alexander V. Gasnikov +3

Second-order methods for smooth monotone variational inequalities reach the optimal rate , but a distributed exact Jacobian costs times more communication than an…

math.OC2026

Application of Optimal Inexact Second-Order Acceleration to Distributed Stochastic Optimization under Statistical Similarity

Yury A. Sokolov, Maxim K. Mashtaler, Alexander V. Gasnikov +3

We consider distributed stochastic convex optimization with a fixed budget of independent samples split among workers. Sample average approximation reduces the problem to a…