9.520/6.860, Class 16

Class 16: Generalization Error and Stability

Instructor: Lorenzo Rosasco


We review the generalization bounds and use stability to prove generalization bounds for Tikhonov regularization in RKHS and iterative regularization, e.g. Stochastic Gradient Descent, via early stopping.

Class Reference Material

L. Rosasco, T. Poggio, Machine Learning: a Regularization Approach, MIT-9.520 Lectures Notes, Manuscript, Dec. 2017

Chapter 2 - Foundational Results

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.

Suggested Reading