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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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DissertationDOI
Bayesian nonparametric clustering in relational and high dimensional settings with applications in bioinformatics
TL;DR: Three feature selection and cross-clustering methods, including an infinite relational model with feature selection (FIRM) which incorporates the rich information of multi-relational data, a deterministic approximation to Cross Dirichlet Process mixture (CDPM) and to cross-Clustering; and a randomized approximation, based on a truncated hierarchy are developed.
Journal ArticleDOI
A semiparametric Bayesian model for multiple monotonically increasing count sequences
TL;DR: In this paper, a hierarchical nonparametric Bayesian model for sequences of monotonically increasing counts was proposed to assess the effectiveness of a treatment in preventing recurrence on subjects affected by bladder cancer.
Journal ArticleDOI
Risk Assessment for Toxicity Experiments with Discrete and Continuous Outcomes: A Bayesian Nonparametric Approach
TL;DR: A Bayesian nonparametric modeling approach to inference and risk assessment for developmental toxicity studies and uses data from a toxicity experiment that investigated the toxic effects of an organic solvent to demonstrate the range of inferences obtained from the non Parametric mixture model, including comparison with a parametric hierarchical model.
Proceedings ArticleDOI
N-gram over Context
TL;DR: Experiments on review articles/papers/tweet show that NOC is useful as a generative model to discover both the topic structure and the corresponding N-grams, and well complements human experts and domain specific knowledge.
Multi-Label Answer Aggregation for Crowdsourcing
TL;DR: This paper proposes a novel Bayesian nonparametric model for multi-label answer aggregation that enables us to predict labels for non-grounded items, while taking into account dependencies between the labels in different answer sets.
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.