MCMC and Naive Parallel Gibbs Sampling
نویسندگان
چکیده
In this scribe, we are going to review the Parallel Monte Carlo Markov Chain (MCMC) method. First, we will recap of MCMC methods, particularly the Metropolis-Hasting and Gibbs Sampling algorithms. Then we will show the drawbacks of these classical MCMC methods as well as the Naive Parallel Gibbs Sampling approach. Finally, we will come up with the Sequential Monte Carlo and Parallel Inference for Bayesian nonparametric models, specifically, the Dirichlet Process Mixture model. Numerous kinds of inference techniques are also discussed in this paper.
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