Lecture 17: Bayesian Interpretations of Regularization
Charlie Frogner
Description
We describe probabilistic interpretations of Tikhonov regularization, focusing on regularized least squares. We show how ERM, linear RLS and kernel RLS can be derived in a Bayesian framework and discuss implications and possible limitations.
Slides
Slides for this lecture: PDF
Suggested Reading
- Vladimir I. Bogachev Gaussian Measures. Mathematical Surveys and Monographs, Volume 62, American Mathematical Society, 1998.