Online Learning with Self-tuned Gaussian Kernels: Good Kernel-initialization by Multiscale Screening

Masa Aki Takizawa, Masahiro Yukawa

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

    Abstract

    We propose an efficient adaptive update method for the kernel parameters: the kernel coefficients, scales and centers. The mirror descent and the steepest descent method for squared error cost function are employed to update the kernel scales and centers, respectively. Although the problem considered in this paper is nonconvex, we reduce the possibility of falling into local minima by using a novel multiple initialization scheme to grow the dictionary without great increases of the dictionary size. Through computer experiments, we show that the proposed algorithm enjoys a high adaptation-capability while maintaining a small dictionary size, without detailed tuning of the initial kernel parameters.

    Original languageEnglish
    Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages4863-4867
    Number of pages5
    ISBN (Electronic)9781479981311
    DOIs
    Publication statusPublished - 2019 May 1
    Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
    Duration: 2019 May 122019 May 17

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume2019-May
    ISSN (Print)1520-6149

    Conference

    Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
    CountryUnited Kingdom
    CityBrighton
    Period19/5/1219/5/17

    Keywords

    • automatic parameter tuning
    • dictionary learning
    • Gaussian kernel
    • nonlinear adaptive estimation

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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  • Cite this

    Takizawa, M. A., & Yukawa, M. (2019). Online Learning with Self-tuned Gaussian Kernels: Good Kernel-initialization by Multiscale Screening. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (pp. 4863-4867). [8683899] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2019.8683899