Primal-dual mirror descent for the stochastic programming problems with functional constraints
Optimization and Control
2017-08-01 v9
Abstract
We propose primal-dual stochastic mirror descent for the convex optimization problems with functional constraints. We obtain the rate of convergence in terms of probability of large deviations.
Cite
@article{arxiv.1604.08194,
title = {Primal-dual mirror descent for the stochastic programming problems with functional constraints},
author = {Anastasia Bayandina and Alexander Gasnikov and Evgenia Gasnikova and Sergey Matsievsky},
journal= {arXiv preprint arXiv:1604.08194},
year = {2017}
}
Comments
9 pages, in Russian. Comp. Math. & Mat. Phys. 2018. V. 58