Iterative regularization for learning with convex loss functions

We consider the problem of supervised learning with convex loss functions and propose a new form of iterative regularization based on the subgradient method. Unlike other regularization approaches, in iterative regularization no constraint or penalization is considered, and generalization is achieve...

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Bibliographic Details
Main Authors: Lin, Junhong (Author), Zhou, Ding-Xuan (Author), Rosasco, Lorenzo (Contributor)
Other Authors: McGovern Institute for Brain Research at MIT (Contributor)
Format: Article
Language:English
Published: JMLR, Inc., 2018-06-14T13:35:21Z.
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