A short introduction to learning with kernels

Bernhard Schölkopf*, Alexander J. Smola

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    64 Citations (Scopus)

    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 ν-trick, various kernels and an overview over applications of kernel methods.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    EditorsShahar Mendelson, Alexander J. Smola
    PublisherSpringer Verlag
    Pages41-64
    Number of pages24
    ISBN (Print)9783540005292
    DOIs
    Publication statusPublished - 2003

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume2600
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

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