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On the performance of kernel classes

Date

Authors

Mendelson, Shahar

Publisher

MIT Press

Abstract

We present sharp bounds on the localized Rademacher averages of the unit ball in a reproducing kernel Hilbert space in terms of the eigenvalues of the integral operator associated with the kernel. We use this result to estimate the performance of the empirical minimization algorithm when the base class is the unit ball of the reproducing kernel Hilbert space.

Keywords

Keywords: Algorithms; Approximation theory; Eigenvalues and eigenfunctions; Functions; Mathematical operators; Probability; Theorem proving; Feature map; Hilbert space; Integral operators; Kernel classes; Learning systems

Citation

Journal of Machine Learning Research 4 (2003): 759-771

URI

http://hdl.handle.net/10440/303
http://digitalcollections.anu.edu.au/handle/10440/303

Collections

ANU Research Publications

Source

Journal of Machine Learning Research

Type

Journal article

DOI

10.1162/1532443041424337

Downloads

File

Description

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