8 citations · 24 across the 24 of their papers we have counts for
5 papers · 1 filter
Development of a method for solving structural optimization problems
Alexander Tyurin
In practice, optimization tasks have some structure that allows developing new algorithms for every problem with faster convergence rates. Using the structure of optimization tasks…
Accelerated and nonaccelerated stochastic gradient descent with inexact model
Darina Dvinskikh, Alexander Tyurin, Alexander Gasnikov +1
In this paper, we propose a new way to obtain optimal convergence rates for smooth stochastic (strong) convex optimization tasks. Our approach is based on results for optimization…
Oracle Complexity Separation in Convex Optimization
Anastasiya Ivanova, Evgeniya Vorontsova, Dmitry Pasechnyuk +4
Many convex optimization problems have structured objective function written as a sum of functions with different types of oracles (full gradient, coordinate derivative, stochastic…
Inexact Relative Smoothness and Strong Convexity for Optimization and Variational Inequalities by Inexact Model
Fedor Stonyakin, Alexander Tyurin, Alexander Gasnikov +7
In this paper, we propose a general algorithmic framework for first-order methods in optimization in a broad sense, including minimization problems, saddle-point problems, and vari…
Accelerated and nonaccelerated stochastic gradient descent with model conception
Darina Dvinskikh, Alexander Tyurin, Alexander Gasnikov +1
In this paper, we describe a new way to get convergence rates for optimal methods in smooth (strongly) convex optimization tasks. Our approach is based on results for tasks where g…