Effects of norms on learning properties of support vector machines

Kazushi Ikeda, Noboru Murata

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

    1 Citation (Scopus)

    Abstract

    Support Vector Machines (SVMs) are known to have 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 Lp norm instead of the L2 norm. In this paper, we theoretically show the effects of p on the learning properties of SVMs by clarifying its geometrical meaning.

    Original languageEnglish
    Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    VolumeV
    ISBN (Print)0780388747, 9780780388741
    DOIs
    Publication statusPublished - 2005
    Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA
    Duration: 2005 Mar 182005 Mar 23

    Other

    Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
    CityPhiladelphia, PA
    Period05/3/1805/3/23

    Fingerprint

    norms
    learning
    Support vector machines
    quadratic programming
    Quadratic programming
    programming
    margins

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Signal Processing
    • Acoustics and Ultrasonics

    Cite this

    Ikeda, K., & Murata, N. (2005). Effects of norms on learning properties of support vector machines. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. V). [1416285] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2005.1416285

    Effects of norms on learning properties of support vector machines. / Ikeda, Kazushi; Murata, Noboru.

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. V Institute of Electrical and Electronics Engineers Inc., 2005. 1416285.

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

    Ikeda, K & Murata, N 2005, Effects of norms on learning properties of support vector machines. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. vol. V, 1416285, Institute of Electrical and Electronics Engineers Inc., 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05, Philadelphia, PA, 05/3/18. https://doi.org/10.1109/ICASSP.2005.1416285
    Ikeda K, Murata N. Effects of norms on learning properties of support vector machines. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. V. Institute of Electrical and Electronics Engineers Inc. 2005. 1416285 https://doi.org/10.1109/ICASSP.2005.1416285
    Ikeda, Kazushi ; Murata, Noboru. / Effects of norms on learning properties of support vector machines. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. V Institute of Electrical and Electronics Engineers Inc., 2005.
    @inproceedings{a8aea584273e40379fc92921ff158fbb,
    title = "Effects of norms on learning properties of support vector machines",
    abstract = "Support Vector Machines (SVMs) are known to have 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 Lp norm instead of the L2 norm. In this paper, we theoretically show the effects of p on the learning properties of SVMs by clarifying its geometrical meaning.",
    author = "Kazushi Ikeda and Noboru Murata",
    year = "2005",
    doi = "10.1109/ICASSP.2005.1416285",
    language = "English",
    isbn = "0780388747",
    volume = "V",
    booktitle = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
    publisher = "Institute of Electrical and Electronics Engineers Inc.",

    }

    TY - GEN

    T1 - Effects of norms on learning properties of support vector machines

    AU - Ikeda, Kazushi

    AU - Murata, Noboru

    PY - 2005

    Y1 - 2005

    N2 - Support Vector Machines (SVMs) are known to have 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 Lp norm instead of the L2 norm. In this paper, we theoretically show the effects of p on the learning properties of SVMs by clarifying its geometrical meaning.

    AB - Support Vector Machines (SVMs) are known to have 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 Lp norm instead of the L2 norm. In this paper, we theoretically show the effects of p on the learning properties of SVMs by clarifying its geometrical meaning.

    UR - http://www.scopus.com/inward/record.url?scp=33646760980&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=33646760980&partnerID=8YFLogxK

    U2 - 10.1109/ICASSP.2005.1416285

    DO - 10.1109/ICASSP.2005.1416285

    M3 - Conference contribution

    AN - SCOPUS:33646760980

    SN - 0780388747

    SN - 9780780388741

    VL - V

    BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

    PB - Institute of Electrical and Electronics Engineers Inc.

    ER -