A least squares formulation for a class of generalized eigenvalue problems in machine learning

Proceedings of the 26th International Conference On Machine Learning, ICML 2009

Volumn , Issue , 2009, Pages 977-984

  Sun, Liang ^a   Ji, Shuiwang ^a   Ye, Jieping ^a  

^a Arizona State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CANONICAL CORRELATION ANALYSIS; CLASSICAL TECHNIQUES; CONJUGATE GRADIENT; EQUIVALENCE RELATIONSHIP; GENERALIZATION ABILITY; GENERALIZED EIGENVALUE PROBLEMS; LARGE-SCALE PROBLEM; LEAST SQUARES PROBLEMS; LEAST-SQUARES FORMULATION; LINEAR DISCRIMINANT ANALYSIS; MACHINE LEARNING ALGORITHMS; MACHINE-LEARNING; PARTIAL LEAST SQUARES; REGULARIZATION TECHNIQUE; SCALABLE IMPLEMENTATION; SPECTRAL LEARNING;

CONJUGATE GRADIENT METHOD; DISCRIMINANT ANALYSIS; EDUCATION; EIGENVALUES AND EIGENFUNCTIONS; ROBOT LEARNING; SWITCHING SYSTEMS;

LEARNING ALGORITHMS;

EID: 71149101160     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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