lecture07

lecture07 - with beta=O(1/l), and also to bound the loss...

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Lecture 07: Stability of Tikhonov Regularization Alex Rakhlin Description 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
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Unformatted text preview: with beta=O(1/l), and also to bound the loss function. In the process, we will gain additional insight into the mathematics of optimization and RKHS. Suggested Reading O. Bousquet and A. Elisseeff. Stability and Generalization. Journal of Machine Learning Research, to appear, 2002....
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