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Poster

Testing for Homogeneity with Kernel Fisher Discriminant Analysis

Zaid Harchaoui · Francis Bach · Moulines Eric


Abstract:

We propose to test for the homogeneity of two samples by using Kernel Fisher discriminant Analysis. This provides us with a consistent nonparametric test statistic, for which we derive the asymptotic distribution under the null hypothesis. We give experimental evidence of the relevance of our method on both artificial and real datasets.

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