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Issue No.05 - Sept.-Oct. (2013 vol.15)
pp: 9-11
Francis J. Alexander , Los Alamos National Laboratory
The guest editor discusses some recent advances in machine learning and their applications to exciting new problem areas.
Special issues and sections, Computational modeling, Pattern recognition, Machine learning, Scientific computing,scientific computing, machine learning, computational learning, pattern recognition
Francis J. Alexander, "Machine Learning [Guest editor's introduction]", Computing in Science & Engineering, vol.15, no. 5, pp. 9-11, Sept.-Oct. 2013, doi:10.1109/MCSE.2013.107
1. R.O. Duda,P.E. Hart,, and D.G. Stork,Pattern Classification, John Wiley & Sons, 2012.
2. S.S. Haykin,Neural Networks and Learning Machines, vol. 3, Prentice Hall, 2009.
3. M. Minsky and P. Seymour,Perceptrons, MIT Press, 1969.
4. V.N. Vapnik and A.Y. Chervonenkis,“On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities,” Theory of Probability & Its Applications, vol. 16, no. 2, 1971, pp. 264-280.
5. N. Cristianini and J. Shawe-Taylor,An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods,” Cambridge Univ. Press, 2000.
6. Y. Freund et al., “Experiments with a New Boosting Algorithm,” Proc. Int’l Conf. Machine Learning, IEEE, 1996, pp. 148-156.
7. Z.-H. Zhou., Ensemble Methods: Foundations and Algorithms, CRC Press, 2012.
8. T.G. Dietterich et al., “Structured Machine Learning: The Next Ten Years,” Machine Learning, vol. 73, no. 1, 2008, pp. 3-23.
9. N. Cesa-Bianchi,Prediction, Learning, and Games,” Cambridge Univ. Press, 2006.
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