Universal learning technology: Support Vector Machines

NEC Journal of Advanced Technology

Volumn 2, Issue 2, 2005, Pages 137-144

  Vapnik, Vladimir ^a  

^a NEC LABORATORIES AMERICA   (United States)

Author keywords

Pattern recognition; Statistical Learning Theory; Support Vector Machines

Indexed keywords

LEARNING SYSTEMS; MATHEMATICAL MODELS; OPTIMIZATION; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION; STATISTICAL METHODS; VECTORS;

STATISTICAL LEARNING THEORY; SUPPORT VECTOR MACHINES;

INFORMATION TECHNOLOGY;

EID: 23744442946     PISSN: 13488341     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (5)

1. V. Vapnik, "The Nature of Statistical Learning Theory," Springer, 1995.
2. V. Vapnik, "Statistical Learning Theory," J. Wiley, 1998.
3. C. Leslie, E. Eskin, et al., "Mismatch string kernels for discriminative protein classification," Bioinformatics, 20, 4, 2004.
4. J. Weston, F. Peres-Cruz, O. et al., "Feature selection and transduction for prediction of molecular bioactivity for drug design," Bioinformatics, 19, 3, 2003.
5. T. Joachims, "Learning to Classify Text Using Support Vector Machines," Kulwer Academic Publishers, 2002.