Towards understanding why Lookahead generalizes better than SGD and beyond

To train networks, lookahead algorithm [1] updates its fast weights k times via an inner-loop optimizer before updating its slow weights once by using the latest fast weights. Any optimizer, e.g. SGD, can serve as the inner-loop optimizer, and the derived lookahead generally enjoys remarkable test p...

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Main Authors: ZHOU, Pan, YAN, Hanshu, YUAN, Xiaotong, FENG, Jiashi, YAN, Shuicheng
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語言:English
出版: Institutional Knowledge at Singapore Management University 2021
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/8987
https://ink.library.smu.edu.sg/context/sis_research/article/9990/viewcontent/2021_NeurIPS_lookahead.pdf
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機構: Singapore Management University
語言: English

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