8 citations · 24 across the 24 of their papers we have counts for
5 papers · 1 filter
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…
Gradient Methods for Problems with Inexact Model of the Objective
Fedor Stonyakin, Darina Dvinskikh, Pavel Dvurechensky +8
We consider optimization methods for convex minimization problems under inexact information on the objective function. We introduce inexact model of the objective, which as a parti…
Inexact Model: A Framework for Optimization and Variational Inequalities
Fedor Stonyakin, Alexander Gasnikov, Alexander Tyurin +6
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 variat…