期刊
OPTIMIZATION LETTERS
卷 14, 期 7, 页码 1615-1625出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11590-020-01537-8
关键词
Stochastic subgradient method; Nonsmooth optimization; Generalized differentiable functions; Chain rule
资金
- NSF [DMS-1907522]
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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