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We give families of examples where sharp rates of convergence to stationarity of the widely used Gibbs sampler are available. The examples involve standard exponential families and their conjugate pri...
Gibbs Sampling, Conjugate Priors and Coupling
Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance ...
In this paper is proposed a new heuristic approach belonging to the field of evolutionary Estimation of Distribution Algorithms (EDAs). EDAs builds a probability model and a set of solutions is sample...
Abstract: In this paper is proposed a new heuristic approach belonging to the field of evolutionary Estimation of Distribution Algorithms (EDAs). EDAs builds a probability model and a set of solutions...
This note presents a simple and elegant sampler which could be used as an alternative to the reversible jump MCMC methodology.
We give families of examples where sharp rates of convergence to stationarity of the widely used Gibbs sampler are available. The examples involve standard exponential families and their conjugate ...
Let K be a reversible Markov kernel on a measurable space (S,B) with stationary distribution P. Regard K as a linear operator, K:L2(P)→L2(P), and suppose that L2(P) admits an orthonormal basis of ...
It is a pleasure to congratulate the authors for this excellent, original and pedagogical paper. I read a preliminary draft at the end of 2006 and I then mentioned to the authors that their work sh...
We are thankful to the discussants for their hard, interesting work. The main purpose of our paper was to give reasonably sharp rates of convergence for some simple examples of the Gibbs sampler. We...

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