1 Kajile

Variational Inference For Dirichlet Process Mixtures Bibtex Bibliography

  • 2017
  • [j48]

    Truyen Tran, Dinh Quoc Phung, Hung Hai Bui, Svetha Venkatesh:
    Hierarchical semi-Markov conditional random fields for deep recursive sequential data.Artif. Intell.246: 53-85 (2017)

  • [j47]

    Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Duc Thanh Nguyen, John Yearwood, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
    Kernel-based features for predicting population health indices from geocoded social media data.Decision Support Systems102: 22-31 (2017)

  • [j46]

    Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Q. Phung:
    Latent sentiment topic modelling and nonparametric discovery of online mental health-related communities.I. J. Data Science and Analytics4(3): 209-231 (2017)

  • [j45]

    Thin Nguyen, Mark E. Larsen, Bridianne O'Dea, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
    Estimation of the prevalence of adverse drug reactions from social media.I. J. Medical Informatics102: 130-137 (2017)

  • [j44]

    Viet Huynh, Dinh Q. Phung:
    Streaming clustering with Bayesian nonparametric models.Neurocomputing258: 52-62 (2017)

  • [j43]

    Trang Pham, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
    Predicting healthcare trajectories from medical records: A deep learning approach.Journal of Biomedical Informatics69: 218-229 (2017)

  • [j42]

    Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
    Approximation Vector Machines for Large-scale Online Learning.Journal of Machine Learning Research18: 111:1-111:55 (2017)

  • [j41]

    Pratibha Vellanki, Thi V. Duong, Sunil Kumar Gupta, Svetha Venkatesh, Dinh Q. Phung:
    Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data.Knowl. Inf. Syst.51(1): 127-157 (2017)

  • [j40]

    Budhaditya Saha, Sunil Kumar Gupta, Dinh Q. Phung, Svetha Venkatesh:
    Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions.Knowl. Inf. Syst.53(1): 179-206 (2017)

  • [j39]

    Thin Nguyen, Bridianne O'Dea, Mark E. Larsen, Dinh Q. Phung, Svetha Venkatesh, Helen Christensen:
    Using linguistic and topic analysis to classify sub-groups of online depression communities.Multimedia Tools Appl.76(8)

  • Title: Fast search for Dirichlet process mixture models

    Authors:Hal Daumé III

    (Submitted on 10 Jul 2009)

    Abstract: Dirichlet process (DP) mixture models provide a flexible Bayesian framework for density estimation. Unfortunately, their flexibility comes at a cost: inference in DP mixture models is computationally expensive, even when conjugate distributions are used. In the common case when one seeks only a maximum a posteriori assignment of data points to clusters, we show that search algorithms provide a practical alternative to expensive MCMC and variational techniques. When a true posterior sample is desired, the solution found by search can serve as a good initializer for MCMC. Experimental results show that using these techniques is it possible to apply DP mixture models to very large data sets.

    Submission history

    From: Hal Daumé III [view email]
    [v1] Fri, 10 Jul 2009 13:23:37 GMT (177kb)

    Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

    Leave a Comment


    Your email address will not be published. Required fields are marked *