Sparse multinomial logistic regression fast algorithms and generalization bounds

Sparse multinomial logistic regression : fast algorithms and generalization bounds

Recently developed methods for learning sparse classifiers are among the state-of-the-art in supervised learning. These methods learn classifiers that incorporate weighted sums of basis functions with sparsity-promoting priors encouraging the weight estimates to be either significantly large or exac...

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Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1998. - 27(2005), 6 vom: 10. Juni, Seite 957-68
1. Verfasser: Krishnapuram, Balaji (VerfasserIn)
Weitere Verfasser: Carin, Lawrence, Figueiredo, Mário A T, Hartemink, Alexander J
Format: Aufsatz
Sprache:English
Veröffentlicht: 2005
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Evaluation Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.