Infinite tucker decomposition: nonparametric Bayesian models for multiway data analysis

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

Volumn 2, Issue , 2012, Pages 1023-1030

  Xu, Zenglin ^a   Yan, Feng ^a   Qi, Yuan ^b  

^a Purdue University   (United States)

^b PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN MODEL; BINARY DATA; CANDECOMP; CHEMOMETRICS; COMPLEX INTERACTION; COMPUTATIONAL TOOLS; COVARIANCE FUNCTION; DATA ENTITIES; DATA SETS; DATA TYPE; FEATURE SPACE; GAUSSIANS; INFERENCE METHODS; MISSING DATA; MULTI-WAY DATA ANALYSIS; NOISY OBSERVATIONS; NON-PARAMETRIC BAYESIAN; ORDERS OF MAGNITUDE; PREDICTION ACCURACY; PROBABILISTIC FRAMEWORK; SOCIAL NETWORKS; SPACE COMPLEXITY; TENSOR DECOMPOSITION; VARIATIONAL INFERENCE;

BAYESIAN NETWORKS; LEARNING SYSTEMS;

TENSORS;

EID: 84867120756     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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