The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
Abstract. Negotiation plays a fundamental role in systems composed of multiple autonomous agents. Some negotiations may require a more elaborated dialogue where agents would explai...
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
This paper presents new achievements on the automatic mapping of algorithms, written in imperative software programming languages, to custom computing machines. The reconfigurable ...