Bounding the expectation of the supremum of empirical processes indexed by H\"older classes

Schreuder, Nicolas

arXiv.org Machine Learning 

We obtain upper bounds on the expectation of the supremum of empirical processes indexed by H\"older classes of any smoothness and for any distribution supported on a bounded set. Another way to see it is from the point of view of integral probability metrics (IPM), a class of metrics on the space of probability measures: our rates quantify how quickly the empirical measure obtained from $n$ independent samples from a probability measure $P$ approaches $P$ with respect to the IPM indexed by H\"older classes. As an extremal case we recover the known rates for the Wassertein-1 distance.

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