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Exact Sampling with Coupled Markov Chains and Applications to Statistical Mechanics
, 1996
"... For many applications it is useful to sample from a finite set of objects in accordance with some particular distribution. One approach is to run an ergodic (i.e., irreducible aperiodic) Markov chain whose stationary distribution is the desired distribution on this set; after the Markov chain has ..."
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Cited by 548 (13 self)
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For many applications it is useful to sample from a finite set of objects in accordance with some particular distribution. One approach is to run an ergodic (i.e., irreducible aperiodic) Markov chain whose stationary distribution is the desired distribution on this set; after the Markov chain
CircularlyCoupled Markov Chain Sampling
, 2002
"... I show how to run an Ntimestep Markov chain simulation in a circular fashion, so that the state at time 0 follows the state at time N1 in the same way as states at times t follow those at times t1 for 0< t <N . This wraparound of the chain is achieved using a coupling procedure, and produ ..."
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Cited by 8 (2 self)
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I show how to run an Ntimestep Markov chain simulation in a circular fashion, so that the state at time 0 follows the state at time N1 in the same way as states at times t follow those at times t1 for 0< t <N . This wraparound of the chain is achieved using a coupling procedure
OPTIMAL SCALING OF METROPOLISCOUPLED MARKOV Chain Monte Carlo
, 2009
"... We consider optimal temperature spacings for Metropoliscoupled Markov Chain Monte Carlo (mcmcmc) and Simulated Tempering algorithms. We prove ..."
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We consider optimal temperature spacings for Metropoliscoupled Markov Chain Monte Carlo (mcmcmc) and Simulated Tempering algorithms. We prove
Modeling Conversational Interaction Using Coupled Markov Chains
 In DiSSLPSS Joint Workshop
, 2010
"... This paper presents a series of experiments on automatic transcription and classification of fillers and feedbacks in conversational speech corpora. A feature combination of PCA projected normalized F0 ConstantQ Cepstra and MFCCs has shown to be effective for standard Hidden Markov Models (HMM). We ..."
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Cited by 3 (1 self)
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automatic transcription of feedback and fillers in socializing conversations. Index Terms: fillers, feedbacks, coupled hidden markov models, crossspeaker modeling, conversation
Border Sampling Through Coupling Markov Chain Monte Carlo
"... Recently, Progressive Border Sampling (PBS) was proposed for sample selection in supervised learning by progressively learning an augmented full border from small labeled datasets. However, this quadratic learning algorithm is inapplicable to large datasets. In this paper, we incorporate the PBS to ..."
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to a state of the art technique called Coupling Markov Chain Monte Carlo (CMCMC) in an attempt to scale the original algorithm up on large labeled datasets. The CMCMC can produce an exact sample while a naive strategy for Markov Chain Monte Carlo cannot guarantee the convergence to a stationary
Parallel MetropolisCoupled Markov Chain Monte Carlo for Bayesian Phylogenetic Inference
, 2003
"... Motivation: Bayesian estimation of phylogeny is based on the posterior probability distribution of trees. Currently, the only numerical method that can effectively approximate posterior probabilities of trees is Markov Chain Monte Carlo (MCMC). Standard implementations of MCMC can be prone to entrap ..."
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Cited by 27 (1 self)
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Motivation: Bayesian estimation of phylogeny is based on the posterior probability distribution of trees. Currently, the only numerical method that can effectively approximate posterior probabilities of trees is Markov Chain Monte Carlo (MCMC). Standard implementations of MCMC can be prone
A Coupled Markov Chain Approach to Credit Risk Modeling∗
"... ePubWU, the institutional repository of the WU Vienna University of Economics and Business, is provided by the University Library and the ITServices. The aim is to enable open access to the scholarly output of the WU. This document is the version accepted for publication and — in case of peer revie ..."
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ePubWU, the institutional repository of the WU Vienna University of Economics and Business, is provided by the University Library and the ITServices. The aim is to enable open access to the scholarly output of the WU. This document is the version accepted for publication and — in case of peer review — incorporates referee comments. There are minor differences between this and the publisher version which could however affect a citation.
A Coupled Markov Chain Approach to Risk Analysis of Credit Default Swap Index Products∗
, 2009
"... We apply a Coupled Markov Chain approach to model rating transitions and thereby default probabilities of companies. We estimate parameters by applying a maximum likelihood estimation using a large set of historical ratings. Given the parameters the model can be used to simulate scenarios for joint ..."
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We apply a Coupled Markov Chain approach to model rating transitions and thereby default probabilities of companies. We estimate parameters by applying a maximum likelihood estimation using a large set of historical ratings. Given the parameters the model can be used to simulate scenarios
Results 1  10
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603,848