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Fast Search for Distance Dependent Chinese Restaurant Processes

Authors:

Weiwei Feng,

Peng Wang,

Chuan Zhou,

Li Guo,

Peng ZhangAuthors Info & Claims

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

Pages 33 - 34

https://doi.org/10.1145/2740908.2742746

Published: 18 May 2015 Publication History

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Abstract

The distance dependent Chinese Restaurant Processes(dd-CRP), a nonparametric Bayesian model, can model distance sensitive data. Existing inference algorithms for dd-CRP, such as Markov Chain Monte Carlo (MCMC) and variational algorithms, are inefficient and unable to handle massive online data, because posterior distributions of dd-CRP are not marginal invariant. To solve this problem, we present a fast inference algorithm for dd-CRP based on the A-star search. Experimental results show that the new search algorithm is faster than existing dd-CRP inference algorithms with comparable results.

References

[1]

S. Bartunov and D. Vetrov. Variational inference for sequential distance dependent chinese restaurant process. In Proceedings of the 31st International Conference on Machine Learning (ICML-14), pages 1404--1412, 2014.

Google Scholar

[2]

D. M. Blei and P. I. Frazier. Distance dependent chinese restaurant processes. The Journal of Machine Learning Research, 12:2461--2488, 2011.

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Google Scholar

[3]

H. Daumé III. Fast search for dirichlet process mixture models. arXiv preprint arXiv:0907.1812, 2009.

Google Scholar

[4]

R. M. Neal. Markov chain sampling methods for dirichlet process mixture models. Journal of computational and graphical statistics, 9(2):249--265, 2000.

Google Scholar

[5]

W. Zeng and R. Church. Finding shortest paths on real road networks: the case for a*. International Journal of Geographical Information Science, 23(4):531--543, 2009.

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Index Terms

Fast Search for Distance Dependent Chinese Restaurant Processes
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Scientific visualization
2. Information systems
  1. Information systems applications
    1. Data mining

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Information & Contributors

Information

Published In

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

May 2015

1602 pages

ISBN:9781450334730

DOI:10.1145/2740908

General Chairs:
Aldo Gangemi
National Research Council, Italy & Paris 13 University-CNRS, France
,
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 May 2015

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Funding Sources

the Strategic Leading Science and Technology Projects of CAS
the NSFC
Australia ARC Discovery Project
973 project

Conference

WWW '15

Sponsor:

IW3C2

WWW '15: 24th International World Wide Web Conference

May 18 - 22, 2015

Florence, Italy

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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