Learning properties of support vector machines with p-norm

Kazushi Ikeda, Noboru Murata

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    Support Vector Machines (SVMs) are a new classification technique which has a high generalization ability, yet a heavy computational load since margin maximization results in a quadratic programming problem. It is known that this maximization task results in a pth-order programming problem if we employ the p-norm instead of the Euclidean norm, that is. When p = 1, for example, it is a linear programming problem with a much lower computational load. In this article, we theoretically show that p has very little affect on the generalization performance of SVMs in practice by considering its geometrical meaning.

    Original languageEnglish
    Title of host publicationMidwest Symposium on Circuits and Systems
    Volume3
    Publication statusPublished - 2004
    EventThe 2004 47th Midwest Symposium on Circuits and Systems - Conference Proceedings - Hiroshima, Japan
    Duration: 2004 Jul 252004 Jul 28

    Other

    OtherThe 2004 47th Midwest Symposium on Circuits and Systems - Conference Proceedings
    CountryJapan
    CityHiroshima
    Period04/7/2504/7/28

    Fingerprint

    Support vector machines
    Quadratic programming
    Linear programming

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Electronic, Optical and Magnetic Materials

    Cite this

    Ikeda, K., & Murata, N. (2004). Learning properties of support vector machines with p-norm. In Midwest Symposium on Circuits and Systems (Vol. 3)

    Learning properties of support vector machines with p-norm. / Ikeda, Kazushi; Murata, Noboru.

    Midwest Symposium on Circuits and Systems. Vol. 3 2004.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Ikeda, K & Murata, N 2004, Learning properties of support vector machines with p-norm. in Midwest Symposium on Circuits and Systems. vol. 3, The 2004 47th Midwest Symposium on Circuits and Systems - Conference Proceedings, Hiroshima, Japan, 04/7/25.
    Ikeda K, Murata N. Learning properties of support vector machines with p-norm. In Midwest Symposium on Circuits and Systems. Vol. 3. 2004
    Ikeda, Kazushi ; Murata, Noboru. / Learning properties of support vector machines with p-norm. Midwest Symposium on Circuits and Systems. Vol. 3 2004.
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