Stability of Tikhonov Regularization
Lorenzo Rosasco and Tomaso Poggio
We briefly review the generalization bounds of last lecture before
turning to our main goal -- using the stability approach to prove
generalization bounds for Tikhonov regularization in RKHS. In order
to apply the bounds, we need to prove that Tikhonov regularization is
uniformly stable with beta=O(1/n), and also to bound the loss function.
In the process, we will gain additional insight into the
mathematics of optimization and RKHS.
Slides for this lecture: PDF