Partially labeled classification with Markov random walks

@inproceedings{citeulike:1705031, 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...}, author = {Szummer, Martin and Jaakkola, Tommi }, booktitle = {Advances in Neural Information Processing Systems}, citeulike-article-id = {1705031}, keywords = {classification, learning, markov, random, semi-supervised, walks}, posted-at = {2007-11-23 15:49:13}, priority = {4}, title = {Partially labeled classification with Markov random walks}, url = {http://citeseer.ist.psu.edu/495822.html}, volume = {14}, year = {2001} }

TY - CONF ID - citeulike:1705031 L3 - citeulike-article-id:1705031 N2 - 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... TI - Partially labeled classification with Markov random walks VL - 14 T2 - Advances in Neural Information Processing Systems KW - classification KW - learning KW - markov KW - random KW - semi-supervised KW - walks AU - Szummer, Martin AU - Jaakkola, Tommi PY - 2001/// UR - http://citeseer.ist.psu.edu/495822.html ER -