Abstract. This paper examines the effect of cultural learning on a population of neural networks. We compare the genotypic and phenotypic diversity of populations employing only p...
Abstract. In this paper, we consider the possibility of obtaining a kernel machine that is sparse in feature space and smooth in output space. Smooth in output space implies that t...
In many data mining applications, the data manifold is of lower dimension than the dimension of the input space. In this paper, it is proposed to take advantage of this additional ...
We describe a kernel method which uses the maximization of Onicescu’s informational energy as a criteria for computing the relevances of input features. This adaptive relevance d...
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is b...
Wolfram Erlhagen, Albert Mukovskiy, Estela Bicho, ...