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A Kernel Two-Sample Test

Gretton, Arthur; Borgwardt, Karsten; Rasch, Malte J; Schoelkopf, Bernhard; Smola, Alexander


We propose a framework for analyzing and comparing distributions, which we use to construct statistical tests to determine if two samples are drawn from different distributions. Our test statistic is the largest difference in expectations over functions in the unit ball of a reproducing kernel Hilbert space (RKHS), and is called the maximum mean discrepancy (MMD).We present two distributionfree tests based on large deviation bounds for the MMD, and a third test based on the asymptotic...[Show more]

CollectionsANU Research Publications
Date published: 2012
Type: Journal article
Source: Journal of Machine Learning Research


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