TY - GEN
T1 - Tighter variational representations of f-divergences via restriction to probability measures
AU - Ruderman, Avraham
AU - Reid, Mark D.
AU - García-García, Dario
AU - Petterson, James
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84867136405&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9781450312851
T3 - Proceedings of the 29th International Conference on Machine Learning, ICML 2012
SP - 671
EP - 678
BT - Proceedings of the 29th International Conference on Machine Learning, ICML 2012
T2 - 29th International Conference on Machine Learning, ICML 2012
Y2 - 26 June 2012 through 1 July 2012
ER -