The selection of features that are relevant for a prediction or classification problem is an important problem in many domains involving high-dimensional data. Selecting features h...
Michel Verleysen, Fabrice Rossi, Damien Fran&ccedi...
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
We consider an extension of Church’s synthesis problem to ordinals by adding limit transitions to graph games. We consider game arenas where these limit transitions are defined...
This paper addresses the image registration problem applying genetic algorithms. The image registration’s objective is the definition of a mapping that best match two set of poi...
In this paper we apply three Neuro-Evolution (NE) methods as controller design approaches in a collective behavior task. These NE methods are Enforced Sub-Populations, MultiAgent ...