One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...
This paper discusses non-parametric regression between Riemannian manifolds. This learning problem arises frequently in many application areas ranging from signal processing, comp...
The dynamics of the learning equation, which describes the evolution of the synaptic weights, is derived in the situation where the network contains recurrent connections. The deri...
Anthony N. Burkitt, Matthieu Gilson, J. Leo van He...
— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...