Nonparametric Bayesian topic modelling with the hierarchical Pitman-Yor processes

DOI10.1016/j.ijar.2016.07.007zbMathNonearXiv1609.06783OpenAlexW2483632691WikidataQ28111781 ScholiaQ28111781MaRDI QIDQ324682

Lan Du, Kar Wai Lim, Changyou Chen, Wray Buntine

Publication date: 17 October 2016

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1609.06783

zbMATH Keywords

Markov chain Monte CarloBayesian nonparametric methodshierarchical Pitman-Yor processestopic models

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Generalized stochastic processes (60G20)

Related Items (4)

Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes ⋮ Fast approximation of variational Bayes Dirichlet process mixture using the maximization-maximization algorithm ⋮ Hierarchical species sampling models ⋮ A three-way approach for learning rules in automatic knowledge-based topic models

Uses Software

• WinBUGS
• JAGS
• BayesDA
• Equator
• langid.py

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