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, Carreras Perez, Xavier, Collins, Michael
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Association for Computing Machinery 2010
Subjects:
algorithms
design
management
performance
theory
Online Access:http://hdl.handle.net/1721.1/59367

Internet

http://hdl.handle.net/1721.1/59367

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