EE 378A: Reading


Sections of the following books/notes may be useful in parts of this course.

  • Huber, Peter J. Data analysis: what can be learned from the past 50 years. Vol. 874. John Wiley & Sons, 2012.

  • Schölkopf, Bernhard, Luo, Zhiyuan, Vovk, Vladimir (Eds.), Empirical Inference: Festschrift in Honor of Vladimir N. Vapnik, Springer, 2013

  • Vovk V, Papadopoulos H, Gammerman A. (Eds.), Measures of Complexity: Festschrift for Alexey Chervonenkis, Springer, 2015.

  • Lehmann, E.L. and Casella, G., Theory of Point Estimation (Springer Texts in Statistics), 1998.

  • Vapnik, V.N. and Vapnik, V., Statistical learning theory. New York: Wiley, 1998.

  • Devroye, L., Györfi, L. and Lugosi, G., A probabilistic theory of pattern recognition. Springer Science & Business Media, 1996

  • Györfi, L., Kohler, M., Krzyzak, A. and Walk, H., A distribution-free theory of nonparametric regression. Springer Science & Business Media, 2006

  • Catoni, O., 2007. PAC-Bayesian supervised classification: the thermodynamics of statistical learning, IMS Lecture Notes Monogr. Ser., Volume 56, 2007 pdf