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We describe a fast method to eliminate features (variables) in l1 -penalized least-square regression (or LASSO) problems.
Regression shrinkage and selection via the lasso
R. Tibshirani · 1996
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Atomic decomposition by basis pursuit
S.S. Chen, D.L. Donoho, and M.A. Saunders · 2001
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An extensive empirical study of feature selection metrics for text classification
George Forman · 2003
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Convex Optimization
Stephen Boyd and Lieven Vandenberghe · 2004
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Least angle regression (with discussion)
Bradley Efron, Trevor Hastie, Iain Johnstone, and Robert Tibshirani · 2004
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Pathwise coordinate optimization
Jerome Friedman, Trevor Hastie, Holger Höfling, and Robert Tibshirani · 2007
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An interior-point method for large-scale l _ 1 l\_1 -regularized least squares
Seung-Jean Kim, Kwangmoo Koh, Michael Lustig, Stephen Boyd, and Dimitry Gorinevsky · 2007
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An interior-point method for large-scale l _ 1 l\_1 -regularized logistic regression
Kwangmoo Koh, Seung-Jean Kim, and Stephen Boyd · 2007
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L _ 1 L\_1 -regularization path algorithm for generalized linear models
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Fast solution of l _ 1 l\_1 -norm minimization problems when the solution may be sparse
David L. Donoho and Yaakov Tsaig · 2008
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Sure independence screening for ultrahigh dimensional feature space
Jianqing Fan and Jinchi Lv · 2008
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Templates for convex cone problems with applications to sparse signal recovery
A selective overview of variable selection in high dimensional feature space
Jianqing Fan and Jinchi Lv · 2010
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A. Frank and A. Asuncion · 2010
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Regularization paths for generalized linear models via coordinate descent
Jerome Friedman, Trevor Hastie, and Robert Tibshirani · 2010
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Discovering word associations in news media via feature selection and sparse classification
Brian Gawalt, Jinzhu Jia, Luke Miratrix, Laurent El Ghaoui, Bin Yu, and Sophie Clavier · 2010
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Fast l1-minimization algorithms and an application in robust face recognition: a review
A. Yang, A. Ganesh, Z. Zhou, S. Sastry, and Y. Ma · 2010
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S.R. Becker, E.J. Candes, and M. Grant · 2010
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