Primal–Dual Mirror Descent Method for Constraint Stochastic Optimization Problems

被引：0
|
作者：
A. S. Bayandina
A. V. Gasnikov
E. V. Gasnikova
S. V. Matsievskii
机构：
[1] Department of Control and Applied Mathematics,
[2] Moscow Institute of Physics and Technology,undefined
[3] Chair of Mathematical Foundations of Control,undefined
[4] Moscow Institute of Physics and Technology,undefined
[5] Kharkevich Institute for Information Transmission Problems,undefined
[6] Russian Academy of Sciences,undefined
[7] Laboratory of Structural Analysis Methods in Predictive Simulation,undefined
[8] Moscow Institute of Physics and Technology,undefined
[9] Kant Baltic Federal University,undefined
[10] Adygeya State University,undefined
来源：
Computational Mathematics and Mathematical Physics | 2018年 / 58卷
关键词：
Mirror descent method; convex stochastic optimization; constrained optimization; probability of large deviations; randomization;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：1728 / 1736
页数：8
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