Best paper at GECCO conference
The Genetic and Evolutionary Computation Conference (GECCO) conference is the major and most selective yearly conference on evolutionary computation. The paper "Local-Meta-Model CMA-ES for Partially Separable Functions'', of Zyed Bouzarkouna (IFP and Tao project-team), Anne Auger (Tao project-team) et Didier Yu Ding (IFP), obtained the best paper award in the Evolution Strategies / Evolutionary Programming track.
In the context of black-box optimization of numerical objective functions, stochastic search algorithms explore the search space in a random manner and face the so-called curse of dimensionality: the search space volume grows exponentially with the dimension. Consequently problems solved rarely have more than a few hundred of variables. When the problem has some structure like partial separability, exploiting this structure allows to break this curse of dimensionality and hence solve problems with a larger number of variables. This paper is the first to propose an efficient way to exploit partial separability as problem structure within the CMA-ES optimization algorithm coupled with meta-models. It opens the way for other research in this direction.
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Anne Auger , junior research scientist Tao project-team