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» Speeeding Up Markov Chain Monte Carlo Algorithms
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SIGMOD
2011
ACM
250views Database» more  SIGMOD 2011»
12 years 10 months ago
Hybrid in-database inference for declarative information extraction
In the database community, work on information extraction (IE) has centered on two themes: how to effectively manage IE tasks, and how to manage the uncertainties that arise in th...
Daisy Zhe Wang, Michael J. Franklin, Minos N. Garo...
NAACL
2007
13 years 8 months ago
Bayesian Inference for PCFGs via Markov Chain Monte Carlo
This paper presents two Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference of probabilistic context free grammars (PCFGs) from terminal strings, providing an altern...
Mark Johnson, Thomas L. Griffiths, Sharon Goldwate...
IOR
2008
91views more  IOR 2008»
13 years 7 months ago
A Randomized Quasi-Monte Carlo Simulation Method for Markov Chains
We introduce and study a randomized quasi-Monte Carlo method for estimating the state distribution at each step of a Markov chain. The number of steps in the chain can be random an...
Pierre L'Ecuyer, Christian Lécot, Bruno Tuf...
PR
2011
12 years 10 months ago
Generalized darting Monte Carlo
One of the main shortcomings of Markov chain Monte Carlo samplers is their inability to mix between modes of the target distribution. In this paper we show that advance knowledge ...
Cristian Sminchisescu, Max Welling
UAI
2001
13 years 8 months ago
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure
We present a general framework for defining priors on model structure and sampling from the posterior using the Metropolis-Hastings algorithm. The key ideas are that structure pri...
Nicos Angelopoulos, James Cussens