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Machine Learning with Labeled and Unlabeled Data
Tijl De Bie, Thiago Turchetti Maia and Antonio Braga
In: ESANN 2009, 28-30 April 2009, Bruges, Belgium.
AbstractThe field of semi-supervised learning has been expanding rapidly in the past few years, with a sheer increase in the number of related publications. In this paper we present the SSL problem in contrast with supervised and unsupervised learning. In addition, we propose a taxonomy with which we categorize many existing approaches described in the literature based on their underlying framework, data representation, and algorithmic class. | EPrint Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | This is a brief overview paper on SSL, as an introduction to the special session on SSL in ESANN 2009. |
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| Project Keyword: | Project Keyword UNSPECIFIED |
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| Subjects: | Learning/Statistics & Optimisation |
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| ID Code: | 5936 |
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| Deposited By: | Tijl De Bie |
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| Deposited On: | 08 March 2010 |
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