An efficient projection for l1,∞ regularization

An efficient projection for l1,∞ regularization

In recent years the l[subscript 1],[subscript infinity] norm has been proposed for joint regularization. In essence, this type of regularization aims at extending the l[subscript 1] framework for learning sparse models to a setting where the goal is to learn a set of jointly sparse models. In this p...

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Bibliographic Details
Main Authors: Quattoni, Ariadna (Contributor), Carreras Perez, Xavier (Contributor), Collins, Michael (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Association for Computing Machinery, 2010-10-15T15:03:10Z.
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