Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models

NIPS 2006: Proceedings of the 19th International Conference on Neural Information Processing Systems

Volumn , Issue , 2006, Pages 641-648

  Johnson, Mark ^a   Griffiths, Thomas L ^b   Goldwater, Sharon ^c  

^a BROWN UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; CONTEXT FREE GRAMMARS; CONTEXT FREE LANGUAGES;

DIRICHLET PROCESS; HIERARCHICAL DIRICHLET PROCESS; INFERENCE ALGORITHM; NON-PARAMETRIC BAYESIAN MODELING; PROBABILISTIC CONTEXT FREE GRAMMARS; PROBABILISTIC MODELS; PROBABILISTIC RULES; SIMPLE++;

INFERENCE ENGINES;

EID: 79551470241     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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