We investigate different randomizations for mirror descent method. We try to propose such a randomization that allows us to use sparsity of the problem as much as it possible. In the paper one can also find a generalization of randomizaed mirror descent for the convex optimization problems with functional restrictions.
@article{arxiv.1602.00594,
title = {Randomization and sparsity in huge-scale optimization on the Mirror Descent example},
author = {Anton Anikin and Alexander Gasnikov and Alexander Gornov},
journal= {arXiv preprint arXiv:1602.00594},
year = {2016}
}