1 |
Cortes, C. and Vapnik, V. (1995). Support vector network. Machine Learning, 20, 273-297
|
2 |
Gunn, S. (1998). Support vector machines for classification and regression. Technical report, Image Speech and Intelligent Systems Research Group, University of Southampton
|
3 |
Lin, C. F. and Wang, S. D. (2002). Fuzzy support vector machines. IEEE Transactions on Neural Networks, 13, 464-471
DOI
ScienceOn
|
4 |
Mercer, J. (1909). Functions of positive and negative type and their connection with the theory of integral equations. Philosophical Transaction of the Royal Society of London, Ser. A, 209, 415-446
DOI
|
5 |
Scholkopf, B. and Smola, A. J. (2002). Learning with Kernels. MIT Press, Cambridge, MA
|
6 |
Vapnik, V. N. (1995). The Nature of Statistical Learning Theory. Springer-Verlag, Berlin
|
7 |
Vapnik, V. N. (1998). Statistical Learning Theory. Wiley-Interscience, New York
|
8 |
Vapnik, V. N. and Chervonenkis, A. J. (1964). A note on a class of perceptrons. Automation and Remote Control, 25, 112-120
|
9 |
Vapnik, V. and Lerner. L. (1963). Pattern Recognition using generalized portrait method. Automation and Remote Control, 24, 774-780
|