Gibbs sampling for (coupled) infinite mixture models in the stick breaking representation

Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence, UAI 2006

Volumn , Issue , 2006, Pages 385-392

  Porteous, Ian ^a   Ihler, Alex ^a   Smyth, Padhraic ^a   Welling, Max ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADVERSE EFFECT; CAN DESIGN; CLUSTER SIZES; DIRICHLET PROCESS; DIRICHLET PROCESS MIXTURE MODEL; GIBBS SAMPLERS; GIBBS SAMPLING; LANGUAGE MODELING; MIXTURE MODEL; MODELING FLEXIBILITY; NON-PARAMETRIC BAYESIAN; PRIOR DISTRIBUTION; STORM TRAJECTORIES; UNSUPERVISED DATA;

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; COMPUTATIONAL LINGUISTICS; DATA REDUCTION; INFORMATION RETRIEVAL; OBJECT RECOGNITION; UNCERTAINTY ANALYSIS;

MIXTURES;

EID: 80053208868     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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