Partially labeled classification with Markov random walks (2002)
| Venue: | Advances in Neural Information Processing Systems |
| Citations: | 160 - 6 self |
BibTeX
@INPROCEEDINGS{Szummer02partiallylabeled,
author = {Martin Szummer and Tommi Jaakkola},
title = {Partially labeled classification with Markov random walks},
booktitle = {Advances in Neural Information Processing Systems},
year = {2002},
pages = {945--952},
publisher = {MIT Press}
}
Years of Citing Articles
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
To classify a large number of unlabeled examples we combine a limited number of labeled examples with a Markov random walk representation over the unlabeled examples. The random walk representation exploits any low dimensional structure in the data in a robust, probabilistic manner. We develop and compare several estimation criteria/algorithms suited to this representation. This includes in particular multi-way classification with an average margin criterion which permits a closed form solution. The time scale of the random walk regularizes the representation and can be set through a margin-based criterion favoring unambiguous classification. We also extend this basic regularization by adapting time scales for individual examples. We demonstrate the approach on synthetic examples and on text classification problems.
Citations
No citations identified.
