(Enter summary)
Abstract: We propose the hierarchical Dirichlet process (HDP), a nonparametric
Bayesian model for clustering problems involving multiple groups of
data. Each group of data is modeled with a mixture, with the number of
components being open-ended and inferred automatically by the model. (Update)
Cited by: More
Hierarchical Dirichlet Processes - Yee Whye Teh (2003)
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BibTeX entry: (Update)
Y. W. Teh, M. I. Jordan, M. J. Beal, and D. M. Blei. Hierarchical dirichlet processes. Technical Report 653, Department Of Statistics, UC Berkeley, 2003. http://citeseer.ist.psu.edu/article/teh03hierarchical.html More
@misc{ teh03hierarchical,
author = "Y. Teh and M. Jordan and M. Beal and D. Blei",
title = "Hierarchical dirichlet processes",
text = "Y. W. Teh, M. I. Jordan, M. J. Beal, and D. M. Blei. Hierarchical dirichlet
processes. Technical Report 653, Department Of Statistics, UC Berkeley,
2003.",
year = "2003",
url = "citeseer.ist.psu.edu/article/teh03hierarchical.html" }
Citations (may not include all citations):
168
A Bayesian analysis of some nonparametric problems (context) - Ferguson - 1973
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140
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Markov chain sampling methods for Dirichlet process mixture .. (context) - Neal - 2000
44
A constructive definition of Dirichlet priors (context) - Sethuraman - 1994
31
Estimating mixture of Dirichlet process models
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Exchangeability and related topics (context) - Aldous - 1983
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Variational Algorithms for Approximate Bayesian Inference (context) - Beal - 2004
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Hierarchical topic models and the nested Chinese restaurant ..
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Hierarchical dirichlet processes
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