Coupling from the past

Among Markov chain Monte Carlo (MCMC) algorithms, coupling from the past is a method for sampling from the stationary distribution of a Markov chain… (More)
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Topic mentions per year

Topic mentions per year

1996-2016
05101519962016

Papers overview

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2012
2012
This paper shows how coupling from the past (CFTP) can be used to avoid time and memory bottlenecks in direct local pattern… (More)
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2012
2012
Recent research has focused on sampling online social networks (OSNs) using traditional Markov Chain Monte Carlo (MCMC… (More)
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2010
2010
The coupling-from-the-past (CFTP) algorithm of Propp and Wilson, also called perfect sampling, permits one to sample exactly from… (More)
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2007
2007
In recent years, stochastic descriptions of biochemical reactions based on the Master Equation (ME) have become widespread. These… (More)
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2006
2006
We saw in the last lecture how Markov chains can be useful algorithmically. If we have a probability distribution we’d like to… (More)
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2005
2005
In this paper a stopping criterion for a particular class of evolutionary algorithms is devised. First, a model of a generic… (More)
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2000
2000
We give a new method for generating perfectly random samples from the stationary distribution of a Markov chain. The method is… (More)
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2000
2000
Inference for belief networks using Gibbs sampling produces a distribution for unob­ served variables that differs from the… (More)
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1997
1997
The Markov chain Monte Carlo method is a general technique for obtaining samples from a probability distribution. In earlier work… (More)
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1997
1997
A general framework for exact simulation of Markov random elds using the PropppWilson coupling from the past approach is proposed… (More)
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