1Osuna E, Freund R. Girosi F. Training support vector machines:An application to face detection. Proceedings of CVPR'97, Puerto Rico, 1997
2Platt J C. Fast training of support vector machines using sequential minimal optimization. Scholkoph B, Burges C J C, Smola A J(Eds). Advances in kernel method-support vector learning. Cambridge, MA : MIT Press, 1999. 185 - 208
3Vapnik V N.统计学习理论的本质.张学工译.北京:清华大学出版社,2000
4Zhang X G. Using class-center vectors to build support vector machines. Proceedings of NNSP'99,1999
5Keerthi S S,Shevade S K,Bhattaeharyya C,et al. A Fast Iteratire Nearest Point Algorithm for Support Vector Machine Classifier Design. IEEE transactions on neural networks, 2000, 11(1),124-136
6Sch olkoph B,Smola A J,Bartlett P L, New support vector algorithms. Neural Computation,2000, (12) ; 1207-1245
7Yang M H, Ahuja N. A Geometric Approach to Train Support Vector Machines. Proceedings of CVPR 2000, Hilton Head Island,2000.430-437
8Suykens J A K. Least squares support vector machines Classifiers, Neural Processing Letters,1999,9(3) :293-300
9Keoman V, Hadzic I. Support vectors selection by linear programming. Como, Italy,Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000. 193-198
10Olvi L M, David R M. Successive Overrelaxiation for Support Vector Machines. IEEE Trans On Neural Network, 1999, 10(5) :1032-1037