1[1]Vapnik V N.The nature of statistical learning[M].New York: Springer-Verlag,1995.
2[2]Bernd Heisele.Hierarchical Classification and Feature Reduction for Fast Face Detection with Support Vector Machines[J].Pattern Recognition,2003,36: 2007-2017.
3[3]Lu Chunyu,Yan Pingfan,Zhang Changshui.Face recognition using support vector machine[C].In Proc of ICANN'98,Beijing,1998,652-655.
4[5]Burges C,Schokopf B.Advances in Kernel Methods: Support Vestor Learning[C].Cambridge,MA.MIT Press,1999.185-208.
5[6]Vapnik V N.Estimation of Dependences Based on Empirical Data [ M].New York: Springer-Verlag,1982.
6[7]Vapnik V N.Principles of risk minimization for leraning theory[C].In: Advances in Neural Information Processing Systems 4(Moody J E,Hanson S J,Lippmann R P.eds.),831-838,San Mateo: Morgan Kaufmann,1992.
7[8]Vapnik V N.Estimation of Dependences Based on Empirical Data [ M ].New York: Springer-Verlag,1982.
8[9]Boser B E,Guyon I M,Vapnik V.A Training Algorith for Optional Margin Classifiers[A].Proceedings of The fifth Annual Workshop on Computation Learning Theory[C].Pittsburgth,PA,USA: [s.n,],1992,144- 152.
9[10]Osuna E,Freund R,Girosi F.An improved training algorithm for support vector machines[A].Proceedings of the 1997 IEEE Workshop on Neural Network for Signal Processing[C].New York: IEEE Press,1997.276-285.
10[11]Scholkopf B.Comparing support vector machines with gaussian kernels to radial basis function classifiers[J].IEEE Trans on Signal Pressing,1997,45 :2758-2765.