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...

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Bibliografische gegevens
Hoofdauteurs: Wu, F, Rebeschini, P
Formaat: Conference item
Taal:English
Gepubliceerd in: Neural Information Processing Systems Foundation 2021