Regularization in kernel learning
Published in arXiv (Cornell University) • Jan 13, 2010
NobleIDNI4P01W22R30S57
Authors:,
Shahar Mendelson
Joseph Neeman
Abstract
Under mild assumptions on the kernel, we obtain the best known error rates in a regularized learning scenario taking place in the corresponding reproducing kernel Hilbert space (RKHS). The main novelty in the analysis is a proof that one can use a regularization term that grows significantly slower ...
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