Efficient kernel feature extraction for massive data sets

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2006, Issue , 2006, Pages 724-729

  Tsang, Ivor W ^a   Kocsor, Andras ^b   Kwok, James T ^a  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b UNIVERSITY OF SZEGED   (Hungary)

Author keywords

Kernel Feature Extraction; Scalability; SVM

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; DATA STRUCTURES; LINEAR SYSTEMS; PRINCIPAL COMPONENT ANALYSIS; VECTORS;

DATA SETS; KERNEL FEATURE EXTRACTION; KERNEL PRINCIPAL COMPONENT ANALYSIS (KPCA); MAXIMUM MARGIN DISCRIMINANT ANALYSIS (MMDA);

FEATURE EXTRACTION;

EID: 33749561851     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1150402.1150494     Document Type: Conference Paper

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