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2003

1-norm Support Vector Machines

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1-norm Support Vector Machines
The standard 2-norm SVM is known for its good performance in twoclass classi£cation. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advantage over the standard 2-norm SVM, especially when there are redundant noise features. We also propose an ef£cient algorithm that computes the whole solution path of the 1-norm SVM, hence facilitates adaptive selection of the tuning parameter for the 1-norm SVM.
Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibs
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where NIPS
Authors Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani
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