| This paper proposes a new method to reduce training time for neural nets used as function approximators. This method relies on a geometrical control of Multilayer Perceptrons (MLP). A geometrical initializa-tion gives rst better starting points for the learning process. A geometrical parametriza-tion achieves then a more stable convergence. During the learning process, a dynamic geometrical c...

This paper proposes a new method to reduce training time for neural nets used as function approximators. This method relies on a geometrical control of Multilayer Perceptrons (MLP). A geometrical initialization gives first better starting points for the learning process. A geometrical parametrization achieves then a more stable convergence. During the learning process, a dynamic geometrical con...