Randomization and sparsity in huge-scale optimization on the Mirror Descent example
Anton S. Anikin, Alexander Vladimirovich Gasnikov, Alexander Yu. Gornov · arXiv (Cornell University) · 2016
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.