Class 03: Reproducing Kernel Hilbert Spaces
Instructor: Lorenzo Rosasco
Class Reference Material
L. Rosasco, T. Poggio, Machine Learning: a Regularization Approach, MIT-9.520 Lectures Notes, Manuscript, Dec. 2017
Chapter 3 - Hypothesis Spaces
Note: The course notes, in the form of the circulated book draft is the reference material for this class. Related and older material can be accessed through previous year offerings of the course.
Further Reading
- N. Aronszajn. Theory of reproducing kernels. Transactions of the American Mathematical Society, 686, 337-404, 1950.
- T. Evgeniou, M. Pontil and T. Poggio. Regularization Networks and Support Vector Machines Advances in Computational Mathematics, 2000.
- G. Wahba, Spline Models for Observational Data (Chapter 1), Series in Applied Mathematics, Vol. 59, SIAM, 1990.
- A. Berlinet and C. Thomas-Agnan, Reproducing Kernel Hilbert Spaces in Probability and Statistics, Kluwer Academic Publishers, 2004.