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TAO Research team

Machine Learning and Optimisation

  • Leader : Marc Schoenauer
  • Research center(s) : CRI Saclay - Île-de-France
  • Field : Applied Mathematics, Computation and Simulation
  • Theme : Optimization, machine learning and statistical methods
  • Partner(s) : Université Paris-Sud (Paris 11),CNRS
  • Collaborator(s) : U. PARIS 11 (P.-SUD), CNRS

Team presentation

  • Machine Learning can be viewed as an optimization problem. A critical issue, that lead to the development of the Statistical Learning Theory, is that the objective function (the generalization error) is not exactly known.
  • A common practive of several sub-fields of Evolutionary Computation (e.g. Multi-Objective Optimization, Constraint Handling, Co-evolution) is to gather and later exploit some archive of previously encountered solutions. An efficient use of such archive naturally appeals to Machine Learning techniques.
  • The project TAO, result of a crossover between part of the Fractales group at INRIA Rocquencourt and part of the Inférence et Apprentissage group at LRI, thus aims at exploiting efficiently such a synergy between Machine Learning techniques and Evolutionary Algorithms.

    Research themes

    The main application areas are process control (after having caracterized the defects, the issue of minimizing their frequency naturally arises), some medical applications (like the caracterization of the multi-admitted persons), and intelligent control in robotics.

    International and industrial relations

    TAO members are deeply involved in several European Network of Excellence: Evonet and KDNet (FP5) and the PASCAL project (FP6).

    Keywords: Machine Learning Evolutionary Optimization Data Mining