Belief Propagation (BP) can be very useful and efficient for performing approximate inference on graphs. But when the graph is very highly connected with strong conflicting intera...
Abstract-- The need for efficient computation of approximate global state lies at the heart of a wide range of problems in distributed systems. Examples include routing in the Inte...
This paper analyses the Contrastive Divergence algorithm for learning statistical parameters. We relate the algorithm to the stochastic approximation literature. This enables us t...
We introduce the SoftAllEqual global constraint, which maximizes the number of equalities holding between pairs of assignments to a set of variables. We study the computational com...
— We present here an original approach to test the feasibility of footsteps for a given walking pattern generator. It is based on a new approximation algorithm intended to cope w...
Nicolas Perrin, Olivier Stasse, Florent Lamiraux, ...