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A constructive definition of dirichlet priors
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The article was published on 1991-01-01 and is currently open access. It has received 1560 citations till now. The article focuses on the topics: Hierarchical Dirichlet process & Constructive.read more
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Proceedings ArticleDOI
An Infinite Adaptive Online Learning Model for Segmentation and Classification of Streaming Data
TL;DR: This paper proposes a novel adaptive online system based on Markov switching models with hierarchical Dirichlet process priors capable of segmenting and classifying the streaming data over infinite classes, while meeting the memory and delay constraints of streaming contexts.
Journal ArticleDOI
Synthesizing geocodes to facilitate access to detailed geographical information in large scale administrative data
Joerg Drechsler,Jingchen Hu +1 more
TL;DR: In this paper, the authors investigate whether generating synthetic data can be a viable strategy for providing access to detailed geocoding information for external researchers, without compromising the confidentiality of the units included in the database.
Proceedings Article
Part-of-Speech Induction in Dependency Trees for Statistical Machine Translation
TL;DR: Evaluations of Japanese-to-English translation on the NTCIR-9 data show that the induced Japanese POS tags for dependency trees improve the performance of a forestto-string SMT system.
Proceedings Article
A random finite set model for data clustering
Dinh Phung,Ba-Ngu Vo +1 more
TL;DR: A new class of models for data clustering is proposed that addresses set-valued data as well as unknown number of clusters, using a Dirichlet Process mixture of Poisson random finite sets and an efficient Markov Chain Monte Carlo posterior inference technique that can learn the number of cluster and mixture parameters automatically from the data.
Journal ArticleDOI
Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions
TL;DR: In this paper, the authors used diffusion MRI to estimate fiber bundles connecting different regions of the human brain, and these fiber bundles act as highways for structural interconnections in human brain.
References
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Journal ArticleDOI
A Bayesian Analysis of Some Nonparametric Problems
TL;DR: In this article, a class of prior distributions, called Dirichlet process priors, is proposed for nonparametric problems, for which treatment of many non-parametric statistical problems may be carried out, yielding results that are comparable to the classical theory.
Journal ArticleDOI
Ferguson Distributions Via Polya Urn Schemes
TL;DR: In this article, it was shown that a random probability measure P* on X has a Ferguson distribution with parameter p if for every finite partition (B1, *. *, B) of X, the vector p*(B,), * * *, p *(B) has a Dirichlet distribution with parameters (Bj), *--, cp(B,) (when p(B), = 0, this means p*) = 0 with probability 1).
Journal ArticleDOI
Implicit renewal theory and tails of solutions of random equations
TL;DR: For the solutions of certain random equations, or equivalently the stationary solutions of the random recurrences, the distribution tails are evaluated by renewal-theoretic methods as mentioned in this paper.
Book ChapterDOI
Bayesian density estimation by mixtures of normal distributions
TL;DR: In this article, a mixture of a countable number of normal distributions is used to estimate a density f(x) on the real line, which is then used for kernel estimation.
Journal ArticleDOI
On the Asymptotic Behavior of Bayes' Estimates in the Discrete Case
TL;DR: In this article, it was shown that the posterior probability converges to point mass at the true parameter value among almost all sample sequences (for short, the posterior is consistent; see Definition 1) exactly for parameter values in the topological carrier of the prior.