References
- Furey T.S., Cristianini N., Duffy N., Bedharski D.W., Schummer M. and Haussler D., 'Support vector machine classification and validation of cancer tissue samples using microarray expression data', Bioinformatics, Vol. 16, No. 10, pp. 906-914, 2000 https://doi.org/10.1093/bioinformatics/16.10.906
- Genov, R. and Cauwenberghs, G., 'Kerneltron: support vector 'machine' in silicon', IEEE Transactions on Neural Networks, Vol. 14, No. 5, pp.1426-1434, 2003 https://doi.org/10.1109/TNN.2003.816345
- D. Anguita, A. Boni and S. Ridella, 'A digital architecture for support vector machines: theory, algorithm and FPGA implementation', IEEE Transactions on Neural Networks, Vol. 14, No. 5, pp. 993-1009, 2003 https://doi.org/10.1109/TNN.2003.816033
- D. Anguita, A. Boni and S. Ridella, 'Digital kernel perceptron', Electronics Letters, Vol. 38, No. 10, pp.445-446, 2002 https://doi.org/10.1049/el:20020330
- T.T. Friess, N. Cristianini and C. Campbell, 'The kernel-adatron algorithm: a fast and simple learning procedure for support vector machines', 15th International Conference on Machine Learning, Wisconsin, USA, pp. 188-196, July 1998
- B. Scholkopf and A. J. Smola, Learning with kernels: support vector machines, regularization, optimization, and beyond, MIT Press, 2002
- Vapnik V.N., Statistical Learning Theory, John Wiley and Sons, New Work, 1998
- T. R. Golub, D. K. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J. P. Mesirov, H. Coller, M. L. Loh, J. R. Downing, M. A. caligiuri, C. D. Bloomfield and E. S. Lander, 'Molecular classification of cancer: class discovery and class prediction by gene expression monitoring', Science, Vol. 286, pp. 531-537, 1999 https://doi.org/10.1126/science.286.5439.531
- S. Dudoit, J. Fridlyand and T. P. Speed, 'Comparison of discrimination methods for the classification of tumors using gene expression data', Journal of the American Statistical Association, Vol. 97, No. 457, pp. 77-87, 2002 https://doi.org/10.1198/016214502753479248
- Nello C. and John S. T., An Introduction to Support Vector Machine, Cambridge University Press, 2000