Risk-Based Generalizations of f-divergences
2011
Conference Paper
ei
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.
Author(s): | García-García, D. and von Luxburg, U. and Santos-Rodríguez, R. |
Pages: | 417-424 |
Year: | 2011 |
Month: | July |
Day: | 0 |
Editors: | Getoor, L. , T. Scheffer |
Publisher: | International Machine Learning Society |
Department(s): | Empirische Inferenz |
Bibtex Type: | Conference Paper (inproceedings) |
Event Name: | 28th International Conference on Machine Learning (ICML 2011) |
Event Place: | Bellevue, WA, USA |
Address: | Madison, WI, USA |
Digital: | 0 |
ISBN: | 978-1-450-30619-5 |
Links: |
PDF
Web |
BibTex @inproceedings{GarciaGarciavS2011, title = {Risk-Based Generalizations of f-divergences}, author = {García-García, D. and von Luxburg, U. and Santos-Rodríguez, R.}, pages = {417-424}, editors = {Getoor, L. , T. Scheffer}, publisher = {International Machine Learning Society}, address = {Madison, WI, USA}, month = jul, year = {2011}, doi = {}, month_numeric = {7} } |