Add to ORKGThe mixing time of a Markov chain is the min-imum time t necessary for the total variation distance between the distribution of the Markov chain’s current state Xt and its stationary distri-bution to fall below some ✏> 0. In this paper, we present lower bounds for the mixing time of the Gibbs sampler over Gaussian mixture models with Dirichlet priors. 1
We determine the mixing time (up to a constant factor) of the Markov chain whose state space consist...
AbstractIn an earlier paper [J.J. Hunter, Mixing times with applications to perturbed Markov chains,...
This thesis is concerned with isoperimetric methods for studying the rate at which Markov chains app...
The focus of the thesis is the convergence of irreducible aperiodic homoge- neous Markov chains with...
this paper we consider two Gibbs sampling algorithms. These have been proposed by Escobar (1994) and...
In the past few years we have seen a surge in the theory of finite Markov chains, by way of new tech...
The distribution of the “mixing time” or the “time to stationarity” in a discrete time irreducible M...
Graduation date: 2018Markov chains have long been used to sample from probability distributions and ...
AbstractMixing time quantifies the convergence speed of a Markov chain to the stationary distributio...
International audienceWe establish a link between the maximization of Kolmogorov Sinai entropy (KSE)...
We study convergence properties of MCMC algorithms for mixture models with a Dirichle process mixing...
Markov chain Monte Carlo (MCMC) algorithms are simple and extremely power-ful techniques to sample f...
We analyze the mixing time of a natural local Markov chain (the Glauber dynamics) on configurations...
We continue where we left off last class. All of our results today come from a paper of myself [1], ...
AbstractA measure of the “mixing time” or “time to stationarity” in a finite irreducible discrete ti...
We determine the mixing time (up to a constant factor) of the Markov chain whose state space consist...
AbstractIn an earlier paper [J.J. Hunter, Mixing times with applications to perturbed Markov chains,...
This thesis is concerned with isoperimetric methods for studying the rate at which Markov chains app...
The focus of the thesis is the convergence of irreducible aperiodic homoge- neous Markov chains with...
this paper we consider two Gibbs sampling algorithms. These have been proposed by Escobar (1994) and...
In the past few years we have seen a surge in the theory of finite Markov chains, by way of new tech...
The distribution of the “mixing time” or the “time to stationarity” in a discrete time irreducible M...
Graduation date: 2018Markov chains have long been used to sample from probability distributions and ...
AbstractMixing time quantifies the convergence speed of a Markov chain to the stationary distributio...
International audienceWe establish a link between the maximization of Kolmogorov Sinai entropy (KSE)...
We study convergence properties of MCMC algorithms for mixture models with a Dirichle process mixing...
Markov chain Monte Carlo (MCMC) algorithms are simple and extremely power-ful techniques to sample f...
We analyze the mixing time of a natural local Markov chain (the Glauber dynamics) on configurations...
We continue where we left off last class. All of our results today come from a paper of myself [1], ...
AbstractA measure of the “mixing time” or “time to stationarity” in a finite irreducible discrete ti...
We determine the mixing time (up to a constant factor) of the Markov chain whose state space consist...
AbstractIn an earlier paper [J.J. Hunter, Mixing times with applications to perturbed Markov chains,...
This thesis is concerned with isoperimetric methods for studying the rate at which Markov chains app...