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MAP : CAPES (Brazil)/COFECUB (France) MAP - MAchine Learning: a multistrategy aPproach

Abstract: Taking the advantage of the complementarity of the French and the Brazilian teams, this project puts forward a joint investigation in which novel Machine Learning (ML) techniques, with an emphasis on a multistrategy approach, will be proposed. From a multistrategy approach perspective, the objectives are to study trade-off s between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. Most of the problems approached will be in the context of non-supervised learning or cluster analysis. For example, we will analyze the synergy and trade-offs between constrained clustering by constraint programming (French team) and multiobjective clustering (Brazilian team). The practical aspects of the techniques proposed will be addressed, for example, in the context of mining and modelling biological, textual and temporal data. Another important aim of the project is to stimulate cooperation by bringing the French and the Brazilian researchers/students together to exchange ideas and experiences.

Participating Members

Guillaume CLEUZIOU

Thi-Bich-Hanh DIEP-DAO

Matthieu EXBRAYAT

Marcílio PEREIRA DE SOUTO

Christel VRAIN

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