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Geometric Parameters of Kernel Machines

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Computational Learning Theory (COLT 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2375))

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Abstract

We investigate the fat-shattering dimension and the localized Rademacher averages of kernel machines and their connection to the eigenvalues associated with the kernel.

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Author information

Authors and Affiliations

  1. Computer Sciences Laboratory, RSISE, The Australian National University, Canberra, ACT, 0200, Australia

    Shahar Mendelson

Authors
  1. Shahar Mendelson
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Editor information

Editors and Affiliations

  1. Research School of Information Sciences and Engineering, Australian National University, Canberra, ACT, 0200, Australia

    Jyrki Kivinen

  2. Computer Science Department, University of Illinois at Chicago, 851 S. Morgan St., Chicago, IL, 60607, USA

    Robert H. Sloan

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© 2002 Springer-Verlag Berlin Heidelberg

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Mendelson, S. (2002). Geometric Parameters of Kernel Machines. In: Kivinen, J., Sloan, R.H. (eds) Computational Learning Theory. COLT 2002. Lecture Notes in Computer Science(), vol 2375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45435-7_3

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  • DOI: https://doi.org/10.1007/3-540-45435-7_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43836-6

  • Online ISBN: 978-3-540-45435-9

  • eBook Packages: Springer Book Archive

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