Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces

Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces (2003)

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by Sebastian Mika , Gunnar Rätsch , Jason Weston , Bernhard Schölkopf , Alex Smola , Klaus-robert Müller

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30 - 4 self

BibTeX

@MISC{Mika03constructingdescriptive,
    author = {Sebastian Mika and Gunnar Rätsch and Jason Weston and Bernhard Schölkopf and Alex Smola and Klaus-robert Müller},
    title = {Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces},
    year = {2003}
}

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Abstract

We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinearized variant of the Rayleigh coefficient, we propose nonlinear generalizations of Fisher's discriminant and oriented PCA using support vector kernel functions. Extensive simulations show the utility of our approach.

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