81 citations · 151 across the 12 of their papers we have counts for
18 papers · 1 filter
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…
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…
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…
On Accelerated Methods for Saddle-Point Problems with Composite Structure
Vladislav Tominin, Yaroslav Tominin, Ekaterina Borodich +3
We consider strongly-convex-strongly-concave saddle-point problems with general non-bilinear objective and different condition numbers with respect to the primal and the dual varia…