13 citations · 31 across the 8 of their papers we have counts for
13 papers · 1 filter
Method with Batching for Stochastic Finite-Sum Variational Inequalities in Non-Euclidean Setting
Alexander Pichugin, Maksim Pechin, Aleksandr Beznosikov +2
Variational inequalities are a universal optimization paradigm that incorporate classical minimization and saddle point problems. Nowadays more and more tasks require to consider s…
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity
Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich +2
We study structured convex optimization problems, with additive objective , where is (-strongly) convex, is -smooth and convex, and is -smooth, p…
The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization
Dmitry Kovalev, Alexander Gasnikov
In this paper, we study the fundamental open question of finding the optimal high-order algorithm for solving smooth convex minimization problems. Arjevani et al. (2019) establishe…
The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization
Dmitry Kovalev, Alexander Gasnikov
In this paper, we revisit the smooth and strongly-convex-strongly-concave minimax optimization problem. Zhang et al. (2021) and Ibrahim et al. (2020) established the lower bound $Ω…
Decentralized convex optimization under affine constraints for power systems control
Demyan Yarmoshik, Alexander Rogozin, Oleg. O. Khamisov +2
Modern power systems are now in continuous process of massive changes. Increased penetration of distributed generation, usage of energy storage and controllable demand require intr…
Near-Optimal Decentralized Algorithms for Saddle Point Problems over Time-Varying Networks
Aleksandr Beznosikov, Alexander Rogozin, Dmitry Kovalev +1
Decentralized optimization methods have been in the focus of optimization community due to their scalability, increasing popularity of parallel algorithms and many applications. In…