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MCMC algorithms such as Metropolis-Hastings algorithms are slowed down by the computation of complex target distributions as exemplified by huge datasets.
Theory of Probability
Jeffreys, H · 1939
Earlier work this paper cites.
Estimation of finite mixture distributions by Bayesian sampling
Diebolt, J · 1994
Earlier work this paper cites.
On Markov chain Monte Carlo acceleration
Gelfand, A · 1994
Earlier work this paper cites.
Rates of convergence of the Hastings and Metropolis algorithms
Mengersen, K · 1996
Earlier work this paper cites.
Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
Roberts, G · 1996
Earlier work this paper cites.
Sampling conductivity images via MCMC
Fox, C · 1997
Earlier work this paper cites.
Markov chain Monte Carlo methods based on ‘slicing’ the density function
Neal, R · 1997
Earlier work this paper cites.
Weak convergence and optimal scaling of random walk Metropolis algorithms
Roberts, G. O · 1997
Earlier work this paper cites.
Practical Bayesian density estimation using mixtures of Normals
Roeder, K · 1997
Earlier work this paper cites.
Bayesian Methods for Mixtures of Normal Distributions
Stephens, M · 1997
Earlier work this paper cites.
Reparameterisation strategies for hidden Markov models and Bayesian approaches to maximum likelihood estimation
Robert, C · 1998
Earlier work this paper cites.
A note on Metropolis-Hastings kernels for general state spaces
Tierney, L · 1998
Earlier work this paper cites.
Some adaptive Monte Carlo methods for Bayesian inference
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Finite Mixture Models
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Later among the works it cites.
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Girolami, M · 2011
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Later among the works it cites.
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Later among the works it cites.
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