1. D. Barber, C. Williams, Gaussian processes for Bayesian classification via hybrid Monte Carlo, in: M. Mozer, M. Jordan, T. Petsche (Eds.), Neural Information Processing Systems, Vol. 9, MIT Press, Cambridge, MA, 1997, pp. 340–346.
2. T. Evgeniou, M. Pontil, T. Poggio, A unified framework for regularization networks and support vector machines, A.I. Memo 1654, AI Lab, MIT, MA, 1999.
3. J. Gao, S. Gunn, C. Harris, M. Brown, SVM regression through variational methods and its online implementation, Technical Report, IEEE Trans. Neural Networks, 2000, submitted for publication.
4. A probabilistic framework for SVM regression and error bar estimation;Gao;Mach. Learn.,2002
5. S. Gunn, Support vector machines for classification and regression, Technical Report, ISIS, Department of Electronics and Computer Science, University of Southampton, 1998.