Jump to : Download | Abstract | Contact | BibTex reference | EndNote reference |

ICML:psvm

Felix Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang. $\propto$SVM for learning with label proportions. In International Conference on Machine Learning (ICML) (full oral), Atlanta, GA, June 2013.

Download [help]

Download paper: Adobe portable document (pdf)

Copyright notice:This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

We study the problem of learning with label proportions in which the training data is provided in groups and only the proportion of each class in each group is known. We propose a new method called proportion-SVM, or $\propto$SVM, which explicitly models the latent unknown instance labels together with the known group label proportions in a large-margin framework. Unlike the existing works, our approach avoids making restrictive assumptions about the data. The $\propto$SVM model leads to a non-convex integer programming problem. In order to solve it efficiently, we propose two algorithms: one based on simple alternating optimization and the other based on a convex relaxation. Extensive experiments on standard datasets show that $\propto$SVM outperforms the state-of-the-art, especially for larger group sizes

Contact

FelixX. Yu
Dong Liu
Shih-Fu Chang

BibTex Reference

@InProceedings{ICML:psvm,
   Author = {Yu, Felix and Liu, Dong and Kumar, Sanjiv and Jebara, Tony and Chang, Shih-Fu},
   Title = {$\propto$SVM for learning with label proportions},
   BookTitle = {International Conference on Machine Learning (ICML) (full oral)},
   Address = {Atlanta, GA},
   Month = {June},
   Year = {2013}
}

EndNote Reference [help]

Get EndNote Reference (.ref)

 
bar

For problems or questions regarding this web site contact The Web Master.

This document was translated automatically from BibTEX by bib2html (Copyright 2003 © Eric Marchand, INRIA, Vista Project).