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Lecture 10: 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.