Risk-based generalizations of f-divergences
Date
2011
Authors
Garcia-Garcia, Dario
von Luxburg, Ulrike
Santos-Rodriguez, Raul
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Publisher
OmniPress
Abstract
We derive a generalized notion of f-divergences, called (f,l)-divergences. We show that this generalization enjoys many of the nice properties of/-divergences, although it is a richer family. It also provides alternative definitions of standard divergences in terms of surrogate risks. As a first practical application of this theory, we derive a new estimator for the Kulback-Leibler divergence that we use for clustering sets of vectors.
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Keywords
Keywords: Risk-based; Learning systems
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Source
Max-margin Learning for Lower Linear Envelope Potentials in Binary Markov Random Fields
Type
Conference paper
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Restricted until
2037-12-31