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Cited by 2,120

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Hierarchical Dirichlet Processes

Teh, Yee Whye, Jordan, Michael I, Beal, Matthew J, Blei, David M·2006·Journal of the American Statistical Association
DOI 10.1198/016214506000000302
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Abstract

We consider problems involving groups of data where each observation within a group is a draw from a mixture model and where it is desirable to share mixture components between groups. We assume that the number of mixture components is unknown a priori and is to be inferred from the data. In this setting it is natural to consider sets of Dirichlet processes, one for each group, where the well-known clustering property of the Dirichlet process provides a nonparametric prior for the number of mixture components within each group. Given our desire to tie the mixture models in the various groups, we consider a hierarchical model, specifically one in which the base measure for the child Dirichlet processes is itself distributed according to a Dirichlet process. Such a base measure being discrete, the child Dirichlet processes necessarily share atoms. Thus, as desired, the mixture models in the different groups necessarily share mixture components. We discuss representations of hierarchical Dirichlet processes in terms of a stick-breaking process, and a generalization of the Chinese restaurant process that we refer to as the “Chinese restaurant franchise.” We present Markov chain Monte Carlo algorithms for posterior inference in hierarchical Dirichlet process mixtures and describe applications to problems in information retrieval and text modeling.

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Citations

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Show all 1 references

Research works printed but not linked: 10

  1. Shape Constraints Business, Economic Statistics, 20, 423
  2. Analysis Density Estimation, American Statistical Association, 97, 611
  3. Dirichlet Process Scandinavian, Statistics, 28, 355
  4. Statistical Association, 99, 175
  5. Ser. B, 66, 735
  6. Statistical Analysis, 11, 197
  7. Permutation, Applied Probability, 28, 525
  8. Computing, 11, 501
  9. Sinica, 4, 639
  10. Human Genetics, 68, 978

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Metadata

Authors
Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M.
Affiliations
Yee Whye Teh is Lee Kuan Yew Postdoctoral Fellow, Department of Computer Science, National University of Singapore, Singapore . Michael I. Jordan is Professor of Electrical Engineering and Computer Science and Professor of Statistics, University of California, Berkeley, CA 94720 . Matthew J. Beal is Assistant Professor of Computer Science and Engineering, SUNY Buffalo, Buffalo, NY 14260 . David M. Blei is Assistant Professor of Computer Science, Princeton University, Princeton, NJ . Correspondence...
Venue
Journal of the American Statistical Association
Publisher
Informa UK Limited
Published
2006-12-01
Volume
101
Issue
476
Pages
1566-1581
ISSN
  • 0162-1459
  • 1537-274X
DOI
10.1198/016214506000000302
Cited by
2,120
References
1
Language
en

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