Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization

Variance reduction techniques like SVRG provide simple and fast algorithms for optimizing a convex finite-sum objective. For nonconvex objectives, these techniques can also find a first-order stationary point (with small gradient). However, in nonconvex optimization it is often crucial to find a sec...

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Bibliographic Details
Main Authors: GE, Rong, LI, Zhize, WANG, Weiyao, WANG, Xiang
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2019
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Online Access:https://ink.library.smu.edu.sg/sis_research/8677
https://ink.library.smu.edu.sg/context/sis_research/article/9680/viewcontent/COLT19_stabilizedsvrg.pdf
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Institution: Singapore Management University
Language: English