This paper presents an approach to automatic discovery of functions in Genetic Programming. The approach is based on discovery of useful building blocks by analyzing the evolution...
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Abstract. We provide the first construction of a hash function into ordinary elliptic curves that is indifferentiable from a random oracle, based on Icart's deterministic enco...
In this paper, the N-bit parity problem is solved with a neural network that allows direct connections between the input layer and the output layer. The activation function used i...
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa