Adaptivity of support vector machines with l1 penalty
S.A. van de Geer and B. Tarigan
Technical Report Volume MI 2004-14, 2004.

## Abstract

We consider the problem of adaptation to model complexity and noise level, when using support vector machine loss in binary classification. We show that with $\ell_1$ complexity regularization, adaptive rates can be obtained.

EPrint Type: Article Project Keyword UNSPECIFIED Computational, Information-Theoretic Learning with Statistics 451 Sara van de Geer 23 December 2004