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Boser et al., 1992
Boser, B. E., Guyon, I. M., and Vapnik, V. (1992). A training algorithm for optimum margin classifiers. In Fifth Annual Workshop on Computational Learning Theory, Pittsburgh. ACM.

Bradley and Terry, 1952
Bradley, R. and Terry, M. (1952). The rank analysis of incomplete blcok designs. i. the method of paired comparisions. Biometrics.

Burges and Vapnik, 1995
Burges, C. and Vapnik, V. (1995). A new method for constructing artificial neural networks. Technical report, AT&T, Bell Laboratories, NJ.

Burges, 1998
Burges, C. J. C. (1998). A Tutorial on Support Vector Machines for Pattern Recognition. Kluwer Academic Publishers, Boston.

Cheng and Higham, 1998
Cheng, S. H. and Higham, N. J. (1998). A modified cholesky algorithm based on a symmetric indefinite factorization. SIAM Journal on Matrix Analysis and Applications, 19(4):1097-1110.

Cortes and Vapnik, 1995
Cortes, C. and Vapnik, V. (1995). Support vector networks. Machine Learning, 20:1-25.

Fletcher, 1990
Fletcher, R. (1990). Practical Methods of Optimization. Wiley & Sons, Chichester, UK.

Friedman, 1996
Friedman, J. (1996). Another approach to polychotomous classification. Technical report, Stanford University.

Gill et al., 1991
Gill, P. E., Murray, W., and Wright, M. H. (1991). Numerical Linear Algebra and Optimization, Vol.1. Addison Wesley.

Hastie and Tibshirani, 1996
Hastie, T. and Tibshirani, R. (1996). Classification by pairwise coupling. Technical report, Stanford University and University of Toronto.

Joachims, 1997
Joachims, T. (1997). Svm light: Implementation of the decomposition training algorithm. Bell Lab. Lucent Technologies.

More and Toraldo, 1991a
More, J. and Toraldo, G. (1991a). On the solution of large qp problems with bound constraints. SIAM J. Optimization.

More and Toraldo, 1991b
More, J. J. and Toraldo, g. (1991b). On the solution of large quadratic programming problems with bound constrints. SIAM J. Optimization.

Osuna et al., 1997a
Osuna, E., Freund, R., and Girosi, F. (1997a). An improved training algorithm for support vector machines. In Proc. of IEEE NNSP'97.

Osuna et al., 1997b
Osuna, E. E., Freund, R., and Girosi, F. (1997b). Support vector machines: Training and applications. Technical report, MIT AI Lab. CBCL.

Schmidt and Gish, 1996
Schmidt, M. and Gish, H. (1996). Speaker identification via support vector classifiers. ICASSP, 1:105-108.

Smith, 1998
Smith, N. D. (1998). Support vector machines applied to speech pattern classification. Master's thesis, Cambridge University, Dept. of Engineering.

Spellucci, 1996a
Spellucci, P. (1996a). A new technique for inconsistent qp probelms in the sqp method. Technical report, Dept. of Mathematics, Technical University at Darmstadt.

Spellucci, 1996b
Spellucci, P. (1996b). A sqp method for general nonlinear programs using only equality constrained subproblems. Technical report, Dept. of Mathematics, Technical University at Darmstadt.

Vanderbei, 1994a
Vanderbei, R. J. (1994a). Loqo: An interior point code for quadratic programming. Technical report, Pragram in Statistics & Operations Research, Princeto9n University.

Vanderbei, 1994b
Vanderbei, R. J. (1994b). Symmetric quasi-definite matrices. SIAM J. Optimization.

Vapnik, 1995
Vapnik, V. (1995). The Nature of Statistical Learning Theory, chapter 5. Springer-Verlag, New York.

Weston and Watkins, 1998
Weston, J. and Watkins, C. (1998). Multi-class support vector machines. Technical Report CSD-TR-98-04, Dept. of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, England.

K.K. Chin
Thu Sep 10 11:05:30 BST 1998