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

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