We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
Abstract An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions. Co...
Abstract— In order to reduce computational burden of identification methods for multivariable systems, a hierarchical least squares (HLS) algorithm is developed. The basic idea ...
Abstract. This paper presents a new framework for the motion segmentation and estimation task on sequences of two grey images without a priori information of the number of moving r...
— We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using ...
Ruben Martinez-Cantin, Manuel Lopes, Luis Montesan...