We introduce a new methodology for the exact analysis of M/G/1-type Markov processes. The methodology uses basic, well-known results for Markov chains by exploiting the structure ...
Abstract. We analyse the mixing time of Markov chains using path coupling with stopping times. We apply this approach to two hypergraph problems. We show that the Glauber dynamics ...
We analyse the convergence of a GA when the mutation probability is low and the selection pressure is high, for arbitrary crossover types and probabilities. We succeed in mathemat...
We present algorithms for the generation of uniformly distributed Bayesian networks with constraints on induced width. The algorithms use ergodic Markov chains to generate samples....