Principles of Nonparametric Learning
Suggested readings
N. Cesa-Bianchi, Y. Freund, D. P. Helmbold, D. Haussler, R. Schapire, M. K. Warmuth (1988) “How to use expert advice”, Journal of the ACM, 44, pp. 427–485.
L. Devroye (1987) A Course on Density Estimation, Birkhauser-Verlag.
L. Devroye, L. Györfi (1985) Nonparametric Density Estimation: the L1 View, Wiley.
L. Devroye, L. Györfi, G. Lugosi (1996) Probabilistic Theory of Pattern Recognition, Springer.
M. Kohler (1998) “Nonparametric regression function estimation using interaction least squares splines and complexity regularization”, Metrika, 47, pp. 147–163.
L. Linder, G. Lugosi, K. Zeger (1994) “Rates of convergence in the source coding theorem, in empirical quantizer design, and in universal lossy source coding”, IEEE Trans. Information Theory, 40, pp. 1728–1740.
M. Schoenauer, M. Sebag, F. Jouve, B. Lamy, and H. Maitournam (1996) “Evolutionary identification of macro-mechanical models” In P.J. Angeline and K.E.Kinnear, editors, Advances in Genetic Programming II, pages 467&endash;488, Cambridge, MA, 1996. MIT Press.
N. N. Vapnik (1995) The Nature of Statistical Learning Theory, Springer.