Closed-form supervised dimensionality reduction with generalized linear models

Proceedings of the 25th International Conference on Machine Learning

Volumn , Issue , 2008, Pages 832-839

  Rish, Irina ^a   Grabarnik, Genady ^a   Cecchi, Guillermo ^a   Pereira, Francisco ^b   Gordon, Geoffrey J ^c  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b PRINCETON UNIVERSITY   (United States)

^c Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MACHINE LEARNING; FEATURE EXTRACTION; LEARNING SYSTEMS; ROBOT LEARNING;

CLOSED FORM; DIMENSIONALITY REDUCTION; GENERALIZED LINEAR MODEL; HIGH DIMENSIONAL DATASETS; PREDICTIVE MODELING; REGRESSION PROBLEM; UNIFIED OPTIMIZATION FRAMEWORK;

SUPERVISED LEARNING; LEARNING ALGORITHMS;

CLOSED FORMS; DATA-SETS; DIMENSIONALITY REDUCTIONS; EMPIRICAL RESULTS; GENERALIZED LINEAR MODELS; HIGH-DIMENSIONAL; PREDICTIVE MODELS; REGRESSION PROBLEMS; UNIFIED OPTIMIZATION FRAMEWORKS;

EID: 56449127811     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1390156.1390261     Document Type: Conference Paper

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