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ECML - SUEMA 2010 workshop :
Supervised and Unsupervised Ensemble Methods and their Applications - SUEMA 2010
September 20, 2010 - Barcelona, Spain

Ensembles of supervised learning machines and, in particular, ensembles of classifiers have been established as one of the main research topics in machine learning. Methods for combining unsupervised clusterings have been recently proposed to improve the reliability of clustering algorithms and to assess the validity of discovered clusters. Statistical, algorithmic, representational, computational and practical reasons can explain the success of ensemble methods.
Nevertheless, several problems remain open: for instance in many cases the theoretical reasons of the practical success of several widely used ensemble methods is unclear; the relationships between the diversity and accuracy of base classifiers forming an ensemble and the impact of these characteristics on the effectiveness and the performances of ensemble methods is a controversial question among machine learning researchers; the search of the "best" set of base classifiers or the "best" set of combination methods with respect to the characteristics and the distribution of the data is an open and interesting research line.
Though ensemble methods are subject to intensive research, there are also other open questions, related to real-world applications of such methods. Moreover, innovative applications in the field of unsupervised learning have been recently proposed.
This workshop intends to provide a forum for researchers in the field of Machine Learning and Data Mining to discuss the above and other related topics regarding ensemble methods and their applications.
The workshop is organized with the support of the PASCAL2 (Pattern Analysis, Statistical Modelling and Computational Learning) European Network of Excellence and the DSI, Department of Computer Science of the University of Milan, Italy.