activity
20172024
most citedIntermediate Gradient Methods with Relative Inexactness

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

math.OC20241 cited

Barrier Algorithms for Constrained Non-Convex Optimization

Pavel Dvurechensky, Mathias Staudigl

In this paper we theoretically show that interior-point methods based on self-concordant barriers possess favorable global complexity beyond their standard application area of conv…

math.OC2023

Accuracy Certificates for Convex Minimization with Inexact Oracle

Egor Gladin, Alexander Gasnikov, Pavel Dvurechensky

Accuracy certificates for convex minimization problems allow for online verification of the accuracy of approximate solutions and provide a theoretically valid online stopping crit…

math.OC20231 cited

Intermediate Gradient Methods with Relative Inexactness

Nikita Kornilov, Eduard Gorbunov, Mohammad Alkousa +3

This paper is devoted to first-order algorithms for smooth convex optimization with inexact gradients. Unlike the majority of the literature on this topic, we consider the setting…

math.OC2023

Algorithms for Euclidean-regularised Optimal Transport

Dmitry A. Pasechnyuk, Michael Persiianov, Pavel Dvurechensky +1

This paper addresses the Optimal Transport problem, which is regularized by the square of Euclidean -norm. It offers theoretical guarantees regarding the iteration complexi…

math.OC2017

Parallel algorithms and probability of large deviation for stochastic optimization problems

Pavel Dvurechensky, Alexander Gasnikov, Anastasia Lagunovskaya

We consider convex stochastic optimization problems under different assumptions on the properties of available stochastic subgradient. It is known that, if the value of the objecti…