Research Publications

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Tighter Variational Representations of f-Divergences via Restriction to Probability Measures
Avraham Ruderman, Dario Garcia, James Petterson, Mark Reid
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.
Keywords: divergence, estimation, variational methods

Details

published
Conference Paper
International Conference on Machine Learning (ICML)
361
Edinburgh, Scotland
icml.cc/2012/