Hierarchical Dirichlet Processes
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[1] D. Blackwell,et al. Ferguson Distributions Via Polya Urn Schemes , 1973 .
[2] T. Ferguson. A Bayesian Analysis of Some Nonparametric Problems , 1973 .
[3] C. Antoniak. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems , 1974 .
[4] Michael McGill,et al. Introduction to Modern Information Retrieval , 1983 .
[5] École d'été de probabilités de Saint-Flour,et al. École d'été de probabilités de Saint-Flour XIII - 1983 , 1985 .
[6] D. Aldous. Exchangeability and related topics , 1985 .
[7] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[8] J. Sethuraman. A CONSTRUCTIVE DEFINITION OF DIRICHLET PRIORS , 1991 .
[9] Jayaran Sethuramant. A CONSTRUCTIVE DEFINITION OF DIRICHLET PRIORS , 1991 .
[10] Wolfgang L. Wendland,et al. Variational Methods for BEM , 1991 .
[11] W. Gilks,et al. Adaptive Rejection Sampling for Gibbs Sampling , 1992 .
[12] Andreas Stolcke,et al. Hidden Markov Model} Induction by Bayesian Model Merging , 1992, NIPS.
[13] Radford M. Neal. Bayesian Mixture Modeling , 1992 .
[14] Pietro Muliere,et al. A bayesian predictive approach to sequential search for an optimal dose: Parametric and nonparametric models , 1993 .
[15] David J. C. MacKay,et al. A hierarchical Dirichlet language model , 1995, Natural Language Engineering.
[16] C. Eeden,et al. On using a loss function in selecting the best of two gamma populations in terms of their scale parameters , 1995 .
[17] M. Escobar,et al. Bayesian Density Estimation and Inference Using Mixtures , 1995 .
[18] J. Pitman. Random discrete distributions invariant under size-biased permutation , 1996, Advances in Applied Probability.
[19] J. Skilling,et al. Bayesian Density Estimation , 1996 .
[20] G. Robinson. BOOK REVIEWSBOOK REVIEWS , 1997 .
[21] B. Mallick,et al. Combining information from several experiments with nonparametric priors , 1997 .
[22] S. MacEachern,et al. Estimating mixture of dirichlet process models , 1998 .
[23] G. Tomlinson. Analysis of densities , 1998 .
[24] Durbin,et al. Biological Sequence Analysis , 1998 .
[25] J G Ibrahim,et al. A semi-parametric Bayesian approach to generalized linear mixed models. , 1998, Statistics in medicine.
[26] Sean R. Eddy,et al. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids , 1998 .
[27] Carl E. Rasmussen,et al. The Infinite Gaussian Mixture Model , 1999, NIPS.
[28] Radford M. Neal. Markov Chain Sampling Methods for Dirichlet Process Mixture Models , 2000 .
[29] Sebastian Thrun,et al. Probabilistic Algorithms in Robotics , 2000, AI Mag..
[30] P. Donnelly,et al. Inference of population structure using multilocus genotype data. , 2000, Genetics.
[31] Alan E. Gelfand,et al. SPATIAL NONPARAMETRIC BAYESIAN MODELS , 2001 .
[32] Lancelot F. James,et al. Gibbs Sampling Methods for Stick-Breaking Priors , 2001 .
[33] P. Donnelly,et al. A new statistical method for haplotype reconstruction from population data. , 2001, American journal of human genetics.
[34] Carl E. Rasmussen,et al. Factorial Hidden Markov Models , 1997 .
[35] Alex Acero,et al. Spoken Language Processing , 2001 .
[36] E. Davidson. Genomic Regulatory Systems , 2001 .
[37] P. Green,et al. Modelling Heterogeneity With and Without the Dirichlet Process , 2001 .
[38] Adrian E. Raftery,et al. Model-Based Clustering, Discriminant Analysis, and Density Estimation , 2002 .
[39] H. Ishwaran,et al. Exact and approximate sum representations for the Dirichlet process , 2002 .
[40] S. Gabriel,et al. The Structure of Haplotype Blocks in the Human Genome , 2002, Science.
[41] Giovanni Parmigiani,et al. Semiparametric regression for count data , 2002 .
[42] Gary E. Bolton,et al. Reanalyzing Ultimatum Bargaining—Comparing Nondecreasing Curves Without Shape Constraints , 2002 .
[43] Jean Ponce,et al. Computer Vision: A Modern Approach , 2002 .
[44] Jim Pitman,et al. Poisson–Dirichlet and GEM Invariant Distributions for Split-and-Merge Transformations of an Interval Partition , 2002, Combinatorics, Probability and Computing.
[45] Matthew J. Beal. Variational algorithms for approximate Bayesian inference , 2003 .
[46] Thomas L. Griffiths,et al. Hierarchical Topic Models and the Nested Chinese Restaurant Process , 2003, NIPS.
[47] Michael I. Jordan,et al. Hierarchical Bayesian Models for Applications in Information Retrieval , 2003 .
[48] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[49] S. MacEachern,et al. An ANOVA Model for Dependent Random Measures , 2004 .
[50] P. Müller,et al. A method for combining inference across related nonparametric Bayesian models , 2004 .
[51] Radford M. Neal,et al. A Split-Merge Markov chain Monte Carlo Procedure for the Dirichlet Process Mixture Model , 2004 .
[52] Hemant Ishwaran,et al. Computational Methods for Multiplicative Intensity Models Using Weighted Gamma Processes , 2004 .
[53] J. Pitman. Combinatorial Stochastic Processes , 2006 .