Large Scale Transductive SVMs
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R. Collobert, F. Sinz, J. Weston and L. Bottou. Large Scale Transductive SVMs. Journal of Machine Learning Research, 7:1687-1712, September 2006.
Abstract
We show how the Concave-Convex Procedure can be applied to Transductive SVMs, which traditionally require solving a combinatorial search problem. This provides for the rst time a highly scalable algorithm in the nonlinear case. Detailed experiments verify the utility of our approach. Software is available at http://www.kyb.tuebingen.mpg.de/bs/people/fabee/transduction.html.
BibTeX
@article{collobert:2006a,
author = {R. Collobert and F. Sinz and J. Weston and L. Bottou},
title = {Large Scale Transductive SVMs},
year = {2006},
journal = {Journal of Machine Learning Research},
volume = {7},
pages = {1687-1712},
month = {September}
}
Notes
This is a derivative of the original paper Trading Convexity for Scalability.
Links
- The
UniverSVMsoftware implements algorithms in this paper, based on the SVQP2 optimizer. - DC algorithms
Last modified on Tue Apr 15 17:16:52 2008