Chapter 12
[12:1] Machine Learning: A Probabilistic Perspective §14.1 Kernels Introduction K. Murphy – MIT Press 2012
[12:2] An introduction into protein-sequence annotation A. Muller - Dept. of Biological Sciences, Imperial College Center for Bioinformatics 2002 - http://www.sbg.bio.ic.ac.uk/people/mueller/introPSA.pdf
[12:3] Pattern Recognition and Machine Learning §6.4 Gaussian processes C. Bishop –Springer 2006
[12:4] Introduction to Machine Learning §Nonparametric Regression: Smoothing Models. E. Alpaydin - MIT Press 2007
[12:5] The Elements of Statistical Learning: Data Mining, Inference and Prediction §5.8 Regularization and Reproducing Kernel Hilbert Spaces T. Hastie, R. Tibshirani, J. Friedman - Springer 2001
[12:6] The Elements of Statistical Learning: Data Mining, Inference and Prediction §12.3.2 The SVM as a penalization method. T. Hastie, R. Tibshirani, J. Friedman - Springer 2001
[12:7] A Short Introduction to Learning with Kernels B. Scholkopt...
