This paper concerns the experimental assessment of tempering as a technique for improving Bayesian inference for C&RT models. Full Bayesian inference requires the computation ...
We study the mixing time of some Markov Chains converging to critical physical models. These models are indexed by a parameter β and there exists some critical value βc where th...
Stochastic bounds are a promising method to analyze QoS requirements. Indeed it is sufficient to prove that a bound of the real performance satisfies the guarantee. However, the...
In this paper we study the convergence properties of the power series algorithm, which is a general method to determine (functions of) stationary distributions of Markov chains. W...
We introduce a new probability distribution over a potentially infinite number of binary Markov chains which we call the Markov Indian buffet process. This process extends the IBP...