activity
20172022
most citedADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks

13 citations · 31 across the 8 of their papers we have counts for

collaborators

13 papers

math.OC20225 cited

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…

math.OC20223 cited

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…

math.OC20223 cited

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…

math.OC2022

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…

math.OC20213 cited

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…

math.OC20214 cited

Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks

Dmitry Kovalev, Elnur Gasanov, Peter Richtárik +1

We consider the task of minimizing the sum of smooth and strongly convex functions stored in a decentralized manner across the nodes of a communication network whose links are allo…