Stochastic variance reduced gradient with hyper-gradient for non-convex large-scale learning
Non-convex optimization, which can better capture the problem structure, has received considerable attention in the applications of machine learning, image/signal processing, statistics, etc. With faster convergence rate, there have been tremendous studies on developing stochastic variance reduced a...
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| Published in: | Applied intelligence (Dordrecht, Netherlands) Vol. 53; no. 23; pp. 28627 - 28641 |
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| Main Author: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
Springer US
01.12.2023
Springer Nature B.V |
| Subjects: | |
| ISSN: | 0924-669X, 1573-7497 |
| Online Access: | Get full text |
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