Large Scale Transductive SVMs
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 first 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.
Cite
Text
Collobert et al. "Large Scale Transductive SVMs." Journal of Machine Learning Research, 2006.Markdown
[Collobert et al. "Large Scale Transductive SVMs." Journal of Machine Learning Research, 2006.](https://mlanthology.org/jmlr/2006/collobert2006jmlr-large/)BibTeX
@article{collobert2006jmlr-large,
title = {{Large Scale Transductive SVMs}},
author = {Collobert, Ronan and Sinz, Fabian and Weston, Jason and Bottou, Léon},
journal = {Journal of Machine Learning Research},
year = {2006},
pages = {1687-1712},
volume = {7},
url = {https://mlanthology.org/jmlr/2006/collobert2006jmlr-large/}
}