activity
20182021
most citedADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks

13 citations · 13 across the 2 of their papers we have counts for

collaborators

6 papers

math.OC2021

Non-convex optimization in digital pre-distortion of the signal

Dmitry Pasechnyuk, Alexander Maslovskiy, Alexander Gasnikov +9

In this paper, we give some observation of applying modern optimization methods for functionals describing digital predistortion (DPD) of signals with orthogonal frequency division…

math.OC202113 cited

ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks

Dmitry Kovalev, Egor Shulgin, Peter Richtárik +2

We propose ADOM - an accelerated method for smooth and strongly convex decentralized optimization over time-varying networks. ADOM uses a dual oracle, i.e., we assume access to the…

math.OC2020

Parallel and Distributed algorithms for ML problems

Darina Dvinskikh, Alexander Gasnikov, Alexander Rogozin +1

In this paper we make a survey of modern parallel and distributed approaches to solve sum-type convex minimization problems come from ML applications.

math.OC2020

Fast Linear Convergence of Randomized BFGS

Dmitry Kovalev, Robert M. Gower, Peter Richtárik +1

Since the late 1950's when quasi-Newton methods first appeared, they have become one of the most widely used and efficient algorithmic paradigms for unconstrained optimization. Des…

math.OC2019

Projected Gradient Method for Decentralized Optimization over Time-Varying Networks

Alexander Rogozin, Alexander Gasnikov

Decentralized distributed optimization over time-varying graphs (networks) is nowadays a very popular branch of research in optimization theory and consensus theory. One of the mot…

math.OC2018

Optimal Distributed Optimization on Slowly Time-Varying Graphs

Alexander Rogozin, César A. Uribe, Alexander Gasnikov +2

We study optimal distributed first-order optimization algorithms when the network (i.e., communication constraints between the agents) changes with time. This problem is motivated…