Discriminant analysis: A least squares approximation view

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2005-September, Issue , 2005, Pages

  Zhang, Peng ^a   Peng, Jing ^a   Riedel, Nobert ^b  

^a TULANE UNIVERSITY   (United States)

^b Tulane University   (United States)

Author keywords

Error bound; Kernel trick; Least squares; Linear discriminant analysis; Regularization; Small sample size problem

Indexed keywords

APPROXIMATION ALGORITHMS; COMPUTER VISION; DISCRIMINANT ANALYSIS; FACE RECOGNITION; LEAST SQUARES APPROXIMATIONS; SUPPORT VECTOR MACHINES;

DISCRIMINANT LEARNING ANALYSIS; LEAST SQUARE APPROXIMATIONS; LINEAR DISCRIMINANT ANALYSIS; REGULARIZATION NETWORKS; REGULARIZATION TERMS; SMALL SAMPLE SIZE PROBLEMS; STATISTICAL LEARNING THEORY; SUPPORT VECTOR MACHINE (SVMS);

LEARNING ALGORITHMS;

EID: 80053260141     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2005.444     Document Type: Conference Paper

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