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Abstract: We consider the problem of using a large unlabeled sample to boost performance of a learning algorithm when only a small set of labeled examples is available. In particular, we consider a problem setting motivated by the task of learning to classify web pages, in which the description of each example can be partitioned into two distinct views. For example, the description of a web page can be partitioned into the words occurring on that page, and the words occurring in hyperlinks that point to... (Update)
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BibTeX entry: (Update)
Blum, A., & Mitchell, T. (1998). Combining labeled and unlabeled data with co-training. http://citeseer.ist.psu.edu/blum98combining.html More
@inproceedings{ blum98combining,
author = "Avrim Blum and Tom Mitchell",
title = "Combining Labeled and Unlabeled Data with Co-training",
booktitle = "{COLT}: Proceedings of the Workshop on Computational Learning Theory, Morgan Kaufmann Publishers",
pages = "92-100",
year = "1998",
url = "citeseer.ist.psu.edu/blum98combining.html" }
Citations (may not include all citations):2528 Maximum likelihood from incomplete data via the EM algorithm (context) - Dempster, Laird et al. - 1977
2133 Pattern Classification and Scene Analysis (context) - Duda, Hart - 1973
149 Learning to extract symbolic knowledge from the world wide w.. - Craven, Freitag et al. - 1997
110 Unsupervised word sense disambiguation rivaling supervised m.. - Yarowsky - 1995
107 Efficient noise-tolerant learning from statistical queries - Kearns - 1993
97 A comparison of two learning algorithms for text categorizat.. - Lewis, Ringuette - 1994
76 Supervised learning from incomplete data via an EM approach - Ghahramani, Jordan - 1994
38 Informedia: News-on-demand - multimedia information acquisit.. - Hauptmann, Witbrock - 1997
19 A computational model of teaching - Jackson, Tomkins - 1992
19 Learning from a mixture of labeled and unlabeled examples wi.. - Ratsaby, Venkatesh - 1995
17 and network design problems (context) - Karger, in et al. - 1994
17 and network design problems (context) - Karger, in et al. - 1997
14 Journal of Computer and System Sciences (context) - Goldman, Kearns et al. - 1995
7 Improving acoustic models by watching television - Witbrock, Hauptmann - 1998
3 PAC learning with constantpartition classification noise and.. (context) - Decatur - 1997
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