9.520/6.860, Class 03

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.