PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

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.

Abstract

The 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)
Additional Information:This is a brief overview paper on SSL, as an introduction to the special session on SSL in ESANN 2009.
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5936
Deposited By:Tijl De Bie
Deposited On:08 March 2010