资源论文Risk-Based Generalizations of f -divergences

Risk-Based Generalizations of f -divergences

2020-02-27 | |  52 |   48 |   0

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.

上一篇:Suggesting (More) Friends Using the Implicit Social Graph*

下一篇:Approximate Dynamic Programming for Storage Problems

用户评价
全部评价

热门资源

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...