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 f -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.