lec15 - regularization is uniformly stable with beta=O(1/n...

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Lecture 15: 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
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Unformatted text preview: 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. Suggested Reading • O. Bousquet and A. Elisseeff. Stability and Generalization. Journal of Machine Learning Research, to appear, 2002....
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This note was uploaded on 11/11/2011 for the course BIO 9.07 taught by Professor Ruthrosenholtz during the Spring '04 term at MIT.

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