Robustness of kernel based regression: A comparison of iterative weighting schemes

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5768 LNCS, Issue PART 1, 2009, Pages 100-110

  De Brabanter, Kris ^a   Pelckmans, Kristiaan ^a   De Brabanter, Jos ^a,b   Debruyne, Michiel ^c   Suykens, Johan A K ^a   Hubert, Mia ^a   De Moor, Bart ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b Associatie KULeuven   (Belgium)

^c UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

Kernel methods; Least Squares Support Vector Machines; Reweighting; Robustness

Indexed keywords

FAST CONVERGENCE; KERNEL BASED REGRESSION; KERNEL METHODS; LEAST SQUARE; LEAST SQUARES SUPPORT VECTOR MACHINES; LOSS FUNCTIONS; PRACTICAL GUIDELINES; REAL LIFE DATASETS; REWEIGHTING; ROBUSTNESS; WEIGHT FUNCTIONS; WEIGHTED LEAST SQUARES; WEIGHTING SCHEME;

BACKPROPAGATION; FUNCTION EVALUATION; NEURAL NETWORKS; REGRESSION ANALYSIS; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 70350596405     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04274-4_11     Document Type: Conference Paper

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