Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization∗

被引：0
|
作者：
Li, Zhize [1 ]
Li, Jian [2 ]
机构：
[1] Department of Electrical and Computer Engineering Carnegie Mellon University, Pittsburgh,PA,15213, United States
[2] Institute for Interdisciplinary Information Sciences Tsinghua University, Beijing,100084, China
来源：
Journal of Machine Learning Research | 2022年 / 23卷
基金：
中国国家自然科学基金;
关键词：
Gradient-descent - Local minimums - Nonconvex optimization - Nonconvex-optimization - Optimal algorithm - Proximal gradient descent - Simple++ - Stationary points - Stochastic gradient algorithms - Variance reductions;
D O I：
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