A short introduction to learning with kernels

Authors:
Bernhard Schölkopf;Alexander J. Smola
Affiliations:
Max Planck Institut für Biologische Kybernetik, 72076 Tübingen, Germany;RSISE, The Australian National University, Canberra 0200, ACT, Australia
Venue:
Advanced lectures on machine learning
Year:
2003

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Abstract

We briefly describe the main ideas of statistical learning theory, support vector machines, and kernel feature spaces. This includes a derivation of the support vector optimization problem for classification and regression, the v-trick, various kernels and an overview over applications of kernel methods.