Implicit regularization in matrix sensing via mirror descent
We study discrete-time mirror descent applied to the unregularized empirical risk in matrix sensing. In both the general case of rectangular matrices and the particular case of positive semidefinite matrices, a simple potential-based analysis in terms of the Bregman divergence allows us to establish...
| 主要な著者: | , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Neural Information Processing Systems Foundation
2021
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