A key goal for the perceptual system is to optimally combine
information from all the senses that may be available in order to
develop the most accurate and unified picture possi...
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...
Bayesian recursive inference of phase in additive Gaussian noise environments is studied. A tractable conjugate system is established using a von Mises distribution. Its shaping p...
Anthony Quinn, Jean-Pierre Barbot, Pascal Larzabal
Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from tr...