Adaptive Mirror Descent Methods for Convex Programming Problems with delta-subgradients

Abstract

We propose some adaptive mirror descent dethods for convex programming problems with delta-subgradients and prove some theoretical results.

arXiv commentin Russian

References in corpus (1)

• Mirror Descent for Constrained Optimization Problems with Large Subgradient Values

Cited by in corpus (1)

• Subgradient methods for non-smooth optimization problems with some relaxation of sharp minimum