Revisiting k-means: New algorithms via Bayesian nonparametrics

Proceedings of the 29th International Conference on Machine Learning, ICML 2012

Volumn 1, Issue , 2012, Pages 513-520

  Kulis, Brian ^a   Jordan, Michael I ^b  

^a OHIO STATE UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN MODEL; BAYESIAN NONPARAMETRICS; CLUSTERING APPLICATIONS; CLUSTERING METHODS; DIRICHLET PROCESS MIXTURE; GIBBS SAMPLING; HIERARCHICAL BAYESIAN MODELS; HIERARCHICAL DIRICHLET PROCESS; K-MEANS; K-MEANS CLUSTERING ALGORITHM; MIXTURES OF GAUSSIANS; MULTIPLE DATA; NON-PARAMETRIC; NORMALIZED CUTS; NUMBER OF CLUSTERS;

BAYESIAN NETWORKS; LEARNING SYSTEMS; MIXTURES;

CLUSTERING ALGORITHMS;

EID: 84867132578     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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