References
- N. Cristianini and J. Shawe-Taylor, An introduction tosupport vector machines and other kernel-based learningmethods, Cambridge University Press, 2000
- B. Scholkopf and A. J. Smola, Leaming with kernels,MIT Press, 2002
- K.R. Miiller, S. Mika, G. Ratsch, K. Tsuda, and B.SchQlkopf, 'An introduction to kernel-based learningalgorithms,' IEEE Transactions on Neural Networks, vol.12, no. 2, pp. 181-201, 2001 https://doi.org/10.1109/72.914517
- F. Girosi, 'An equivalence between sparse approximation and support vector machines,' Neural Computation, vol.10, no. 6, pp. 1455-1480, 1998 https://doi.org/10.1162/089976698300017269
- 'The evidence framework applied to supportvector machines,' IEEE Transactions on Neural Networks, vol. 11, no. 5, pp. 1162-1173, 2000 https://doi.org/10.1109/72.870047
- C. Burges, 'A tutorial on support vector machines forpattern recognition,' Knowledge Discovery and Data Mining, vol. 2, no. 2, pp. 121-167, 1998 https://doi.org/10.1023/A:1009715923555
- A. Smola and B. SchQlkopf, 'A tutorial on supportvector regression,' Neuro Colt Technical ReportNC-TR-1998-030, Royal Holloway College, University of London, UK, 1998
- B. Scholkopf, J. C. Platt, J. Shawe-Taylor, and A. J.Smola, and R. C. Williamson, 'Estimating the support ofa high-dimensional distribution,' Neural Computation, vol.13, pp. 1443-1471, 2001 https://doi.org/10.1162/089976601750264965
- G. Ratsch, S. Mika, B. Scholkopf, and K.-R. Miiller,'Constructing boosting algorithms from SVMs: Anapplication to one-class classification,' IEEE Transactionson Pattem Analysis and Machine Intelligence, vol. 24,pp. 1-15, 2002 https://doi.org/10.1109/34.982881
- C. Campbell and K. P. Bennett, 'A linear programmingapproach to novelty detection,' Advances of NIPs 2000,pp. 395-401, 2000
- S. Mika, G. Ratsch, and K.-R. Miiller, 'A mathematicalprogramming approach to the kernel Fisher algorithm,'In T.K. Leen, T.G. Dietterich, and V. TresP, editors,Advances in Neural Information Processing Systems 13,pages 591-597. M1T Press, 2001
- G. Baudat and F. Anouar, 'Generalized discriminntanalysis using a kernel approach,' Neural Computation,vol. 12, no. 10, PP. 2385-2404, 2000 https://doi.org/10.1162/089976600300014980
- S. Mika, G. Ratsch, J. Weston, B. Scholkopf, and K-.-R.Muller, 'Fisher discriminant analysis with kernels,' InY.-H. Hu, J. Larsen, E. Wilson, and S. Douglas,editors, Neural Networks for Signal Processing IX, pp.41-48, IEEE, 1999
- S. Mika, G. Ratsch, J. Weston, and B. Scholkopf.'Invariant feature extraction and classification in kernelspaces,' In S.A. Solla, T.K. Leen, and K..-R. Muller,editors, Advances in Neural Information Processing Systems 12, pp. 526-532, MIT Press, 2000
- A. Smola, T. Friess, and B. Scholkopf, 'SemiparametricSupport Vector and Linear Programming Machines,'Nuero COLT Technical Report Series NC2-TR-1998-052 August, 1998