8 citations · 9 across the 3 of their papers we have counts for
9 papers
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…
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…
Accelerated gradient sliding and variance reduction
Darina Dvinskikh, Sergey Omelchenko, Alexander Tyurin +1
We consider sum-type strongly convex optimization problem (first term) with smooth convex not proximal friendly composite (second term). We show that the complexity of this problem…
Heuristic adaptive fast gradient method in stochastic optimization tasks
Alexander Ogaltsov, Alexander Tyurin
In this paper, we present a heuristic adaptive fast gradient method. We show that in practice our method has a better convergence rate than popular today optimization methods. More…
Primal-dual fast gradient method with a model
Alexander Tyurin
In this work we consider a possibility to use the conception of -model of a function for optimization tasks, whereby solving a primal problem there is a necessity to recove…