Using Sequential Unconstrained Minimization Techniques to simplify SVM solvers

Neurocomputing

Volumn 77, Issue 1, 2012, Pages 253-260

  Joshi, Sachindra ^a   Jayadeva, ^b   Ramakrishnan, Ganesh ^c   Chandra, Suresh ^b  

^a IBM INDIA RESEARCH LAB   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

^c INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

SMO; Support vector machines; SVM

Indexed keywords

BENCHMARK DATASETS; BOX CONSTRAINTS; L-1 NORM SVM; LEAST SQUARE; SEQUENTIAL UNCONSTRAINED MINIMIZATION TECHNIQUES; SMO; SUPPORT VECTOR; SVM; SVM SOLVERS; UNCONSTRAINED OPTIMIZATION PROBLEMS;

LAGRANGE MULTIPLIERS;

SUPPORT VECTOR MACHINES;

ARTICLE; CONTROLLED STUDY; EXPERIMENTAL STUDY; LEARNING ALGORITHM; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL PHENOMENA; PRIORITY JOURNAL; PROBLEM SOLVING; PROCESS OPTIMIZATION; QUALITY CONTROL; REFERENCE DATABASE; SEQUENTIAL UNCONSTRAINED MINIMIZATION TECHNIQUE; SUPPORT VECTOR MACHINE;

EID: 80955130702     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.07.010     Document Type: Article

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