Mean field inference for the Dirichlet process mixture model

DOI10.1214/08-EJS339zbMath1326.62035MaRDI QIDQ1951990

O. Zobay

Publication date: 27 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1244726600

zbMATH Keywords

approximation methodsBayesian nonparametricsdensity estimationvariational inference

Mathematics Subject Classification ID

Density estimation (62G07) Approximations to statistical distributions (nonasymptotic) (62E17)

Related Items

Variational Bayesian inference with Gaussian-mixture approximations

Uses Software

• PRMLT

Cites Work

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• On a class of Bayesian nonparametric estimates: I. Density estimates
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• PRMLT
• A Bayesian analysis of some nonparametric problems
• Sampling the Dirichlet Mixture Model with Slices
• Density Estimation With Confidence Sets Exemplified by Superclusters and Voids in the Galaxies
• Graphical Models, Exponential Families, and Variational Inference
• Estimating Normal Means with a Dirichlet Process Prior
• 10.1162/jmlr.2003.3.4-5.993
• Exact and approximate sum representations for the Dirichlet process
• Gibbs Sampling Methods for Stick-Breaking Priors
• Estimating normal means with a conjugate style dirichlet process prior
• Bayesian Density Estimation and Inference Using Mixtures
• Variational inference for Dirichlet process mixtures
• Convergence properties of a general algorithm for calculating variational Bayesian estimates for a normal mixture model