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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Main Authors: | , , , |
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Format: | text |
Language: | English |
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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 |