Convergence of a stochastic subgradient method with averaging for nonsmooth nonconvex constrained optimization

被引：0
|
作者：
Andrzej Ruszczyński
机构：
[1] Rutgers University,Department of Management Science and Information Systems
来源：
Optimization Letters | 2020年 / 14卷
关键词：
Stochastic subgradient method; Nonsmooth optimization; Generalized differentiable functions; Chain rule;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We prove convergence of a single time-scale stochastic subgradient method with subgradient averaging for constrained problems with a nonsmooth and nonconvex objective function having the property of generalized differentiability. As a tool of our analysis, we also prove a chain rule on a path for such functions.
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页码：1615 / 1625
页数：10
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