Solving Complex Machine Learning Problems with Ensemble Methods


ECML/PKDD 2013, September 27, Prague, Czech Republic

Overview

Ensemble methods are widely utilized within the machine learning community due to their accuracy-improving and robustness attributes. Since even elementary ensemble approaches outperform single learners, multiple classifier systems are the go-to solution in applications where higher predictive performance is required. The emphasis in COPEM is to discuss ensemble strategies that solve difficult machine learning tasks. This workshop will bring together the ensemble method community and researchers that are not ensemble-experts but could benefit from utilizing such techniques to confront interesting research challenges. The goals of COPEM are: a) to discuss state-of-the-art approaches that exploit ensembles to solve complex machine learning problems and, b) to bring the community together and discuss interesting future applications. The ultimate objective of COPEM is not only to present high quality research papers but, even most importantly, to dynamically initiate new collaborations that will work towards new challenges. Following this direction, the workshop will feature networking activities.

News
(28/02/2014) Update on special issue

(12/12/2013) Dealine extension of the special issue:01/01/2014

(28/10/2013) Instructions for authors updated in the Call for special issue
(10/10/2013) Call for special issue here
(5/10/2013) Photos from the workshop here
(23/09/2013) Get the proceedings of the workshop here
Check the program of the workshop here

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Important notice: A selection of the presented papers will invited to submit an extended and revised version for a Special Issue of the Neurocomputing journal