Unsupervised learning of finite mixture models using mean field games

2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011

Volumn , Issue , 2011, Pages 321-328

  Pequito, Sergio ^a,b   Aguiar, A Pedro ^a   Sinopoli, Bruno ^b   Gomes, Diogo A ^c  

^a UNIVERSITY OF LISBON   (Portugal)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

CLOSED FORM SOLUTIONS; CLUSTERING PROBLEMS; EXPECTATION MAXIMIZATION; FINITE MIXTURE MODELS; GAUSSIAN MIXTURE MODEL; GAUSSIANS; GEM ALGORITHM; K DISTRIBUTION; LOG-LIKELIHOOD FUNCTIONS; MEAN FIELD; SPEED OF CONVERGENCE; STATE OF THE ART;

COMMUNICATION; GAME THEORY; IMAGE SEGMENTATION; MAXIMUM LIKELIHOOD;

ALGORITHMS;

EID: 84856082813     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/Allerton.2011.6120185     Document Type: Conference Paper

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