Testing Hypotheses by Regularized Maximum Mean Discrepancy

Abstract — Regularized Maximum Mean Discrepancy (RMMD), our novel measure for kernel-based hypothesis testing, excels at hypothesis tests involving multiple comparisons with power control even when sample sizes are small. We derive asymptotic distributions under the null and alternative hypotheses, and assess power control. Outstanding results are obtained on challenging benchmark datasets. Keywords- kernel-based hypothesis testing, Homogeneity testing, Multiple comparisons, Power I