Stochastic complexities of general mixture models in variational Bayesian learning
type: Item
instance of: scholarly article
title: Stochastic complexities of general mixture models in variational Bayesian learning
zbMATH Open document ID: 1112.68111
author: Kazuho Watanabe
author: Sumio Watanabe
published in: Neural Networks
publication date: 2007-03-27T00:00:00Z
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 5137790
zbMATH Keywords: mixture model
zbMATH Keywords: exponential family
zbMATH Keywords: variational Bayes
zbMATH Keywords: Bayesian learning
zbMATH Keywords: stochastic complexity
zbMATH Keywords: free energy
zbMATH Keywords: Kullback information
zbMATH Keywords: non-regular model
Wikidata QID: Q51935534
MaRDI profile type: Publication
full work available at URL: j.neunet.2006.05.030
OpenAlex ID: W2030085689
cites work: Undamped oscillation of the sample autocovariance function and the effect of prewhitening operation
cites work: On some inequalities for the gamma and psi functions
cites work: Q3995193
cites work: Q5369144
cites work: Testing Homogeneity in Gamma Mixture Models
cites work: Finite mixture models
cites work: Stochastic complexity and modeling
cites work: Online model selection based on the variational Bayes
cites work: Estimating the dimension of a model
cites work: Algorithmic Learning Theory
cites work: Q3093364
cites work: Algebraic analysis for nonidentifiable learning machines
cites work: Singularities in mixture models and upper bounds of stochastic complexity.
DBLP publication ID: journals/nn/WatanabeW07
DOI: 10.1016/J.NEUNET.2006.05.030
description: scientific article; zbMATH DE number 5137790