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Tighter variational representations of f-divergences via restriction to probability measures

Ruderman, Avraham; Garcia-Garcia, Dario; Petterson, James; Reid, Mark


We show that the variational representations for f-divergences currently used in the literature can be tightened. This has implications to a number of methods recently proposed based on this representation. As an example application we use our tighter representation to derive a general f-divergence estimator based on two i.i.d. samples and derive the dual program for this estimator that performs well empirically. We also point out a connection between our estimator and MMD.

CollectionsANU Research Publications
Date published: 2012
Type: Conference paper
Source: Proceedings of the 29th International Conference on Machine Learning, ICML 2012


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