Testing for Homogeneity with Kernel Fisher Discriminant Analysis

Zaid Harchaoui 1 Francis Bach 2 Eric Moulines 1
2 WILLOW - Models of visual object recognition and scene understanding
CNRS - Centre National de la Recherche Scientifique : UMR8548, Inria Paris-Rocquencourt, DI-ENS - Département d'informatique de l'École normale supérieure
Abstract : We propose to investigate test statistics for testing homogeneity in reproducing kernel Hilbert spaces. Asymptotic null distributions under null hypothesis are derived, and consistency against fixed and local alternatives is assessed. Finally, experimental evidence of the performance of the proposed approach on both artificial data and a speaker verification task is provided.
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Submitted on : Monday, April 7, 2008 - 3:36:35 PM
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  • HAL Id : hal-00270806, version 1
  • ARXIV : 0804.1026

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Zaid Harchaoui, Francis Bach, Eric Moulines. Testing for Homogeneity with Kernel Fisher Discriminant Analysis. 2008. ⟨hal-00270806⟩

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