Testing for Homogeneity with Kernel Fisher Discriminant Analysis

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dc.creatorHarchaoui, Zaid
dc.creatorBach, Francis
dc.creatorMoulines, Eric
dc.date2008-04-07
dc.date.accessioned2026-07-07T12:18:10Z
dc.date.available2026-07-07T12:18:10Z
dc.descriptionWe 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.
dc.identifierhttps://arxiv.org/abs/0804.1026
dc.identifierhttp://arxiv.org/abs/0804.1026
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212315
dc.subjectMachine Learning
dc.titleTesting for Homogeneity with Kernel Fisher Discriminant Analysis
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