15 citations · 118 across the 65 of their papers we have counts for
8 papers · 2 filters
Bregman Proximal Method for Efficient Communications under Similarity
Aleksandr Beznosikov, Darina Dvinskikh, Dmitry Bylinkin +2
We propose a novel stochastic distributed method for both monotone and strongly monotone variational inequalities with Lipschitz operator and proper convex regularizers arising in…
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
Aleksei Ustimenko, Aleksandr Beznosikov
In this work, we consider rather general and broad class of Markov chains, Ito chains, that look like Euler-Maryama discretization of some Stochastic Differential Equation. The cha…
Real Acceleration of Communication Process in Distributed Algorithms with Compression
Svetlana Tkachenko, Artem Andreev, Aleksandr Beznosikov +1
Modern applied optimization problems become more and more complex every day. Due to this fact, distributed algorithms that can speed up the process of solving an optimization probl…
Decentralized Optimization Over Slowly Time-Varying Graphs: Algorithms and Lower Bounds
Dmitry Metelev, Aleksandr Beznosikov, Alexander Rogozin +2
We consider a decentralized convex unconstrained optimization problem, where the cost function can be decomposed into a sum of strongly convex and smooth functions, associated with…
Non-Smooth Setting of Stochastic Decentralized Convex Optimization Problem Over Time-Varying Graphs
Aleksandr Lobanov, Andrew Veprikov, Georgiy Konin +3
Distributed optimization has a rich history. It has demonstrated its effectiveness in many machine learning applications, etc. In this paper we study a subclass of distributed opti…
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova +3
This paper delves into stochastic optimization problems that involve Markovian noise. We present a unified approach for the theoretical analysis of first-order gradient methods for…