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, Zhou, Ding-Xuan, Rosasco, Lorenzo
Other Authors: McGovern Institute for Brain Research at MIT
Format: Article
Published: JMLR, Inc. 2018
Online Access:http://hdl.handle.net/1721.1/116303
https://orcid.org/0000-0001-6376-4786