• T. Poggio
  • S. Mukherjee
  • R. Rifkin
  • A. Raklin
  • A. Verri
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 704)


In this chapter we summarize density properties of Reproducing Kernel Hilbert Spaces induced by different classes of kernels. They are important to characterize the power of the associated hypothesis spaces. In the process we characterize the role of b, which is the constant in the standard form of the solution provided by the Support Vector Machine technique \(f(x) = \sum\nolimits_{i = 1}^\ell {\alpha _i } K\left( {x,\:x_i } \right) + b,\) which is a special case of Regularization Machines.


RKHS regularization density 


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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • T. Poggio
    • 1
  • S. Mukherjee
    • 1
  • R. Rifkin
    • 1
  • A. Raklin
    • 1
  • A. Verri
    • 2
  1. 1.McGovern Institute and Center for Biological and Computational Learning Center for Genome ResearchWhitehead Institute Massachusetts Institute of TechnologyCambridgeUSA
  2. 2.INFM - DISIUniversita di GenovaGenovaItaly

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