Regularization in kernel learning

Details Regularization in kernel learning Regularization in kernel learning

2010-01-13

arxiv.org/abs/1001.2094v1

Annals of Statistics 2010, Vol. 38, No. 1, 526-565

Mathematics

Statistics Theory

Published in at http://dx.doi.org/10.1214/09-AOS728 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of

Scientific paper

10.1214/09-AOS728

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 than the
standard quadratic growth in the RKHS norm.

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