We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
We address the problem of learning a kernel for a given supervised learning task. Our approach consists in searching within the convex hull of a prescribed set of basic kernels fo...
Andreas Argyriou, Raphael Hauser, Charles A. Micch...
One of the aims of the Language Technology for eLearning project is to show that Natural Language Processing techniques can be employed to enhance the learning process. To this en...
Active appearance model efficiently aligns objects which are previously modelized in images. We use it for Human Machine Interface (face gesture analysis, lips reading) to modeli...
Yasser Aidarous, Sylvain Le Gallou, Renaud S&eacut...
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...