13 citations · 16 across the 4 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
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.
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…