A novel view of the variational Bayesian clustering

Neurocomputing

Volumn 72, Issue 13-15, 2009, Pages 3366-3369

  Takekawa, Takashi ^a   Fukai, Tomoki ^a,b  

^a RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

^b UNIVERSITY OF TOKYO   (Japan)

Author keywords

Bayesian estimation; Model selection; Robust variational Bayes; Unsupervised learning; Variational approximation

Indexed keywords

BARIUM COMPOUNDS; BAYESIAN NETWORKS; FUNCTION EVALUATION; UNSUPERVISED LEARNING;

BAYESIAN ESTIMATIONS; INFORMATION CRITERION; KULLBACK-LEIBLER DIVERGENCE; MODEL SELECTION; STUDENT'S T DISTRIBUTION; VARIATIONAL APPROXIMATION; VARIATIONAL BAYES; VARIATIONAL BAYESIAN;

CLUSTERING ALGORITHMS;

BAYES THEOREM; LETTER; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MONTE CARLO METHOD; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROBABILITY; STUDENT T TEST;

EID: 74549124423     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2009.04.003     Document Type: Article

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