Tikhonov Regularization and the Representer Theorem

Lorenzo Rosasco


We discuss a fundamental class of learning algorithms the can be interpreted as a form of Tikhonov regularization. Different algorithms correspond to different choices of loss function. Tikhonov regularization provides an estimator which solves a suitable minimization problem. In this class we discuss the properties of this minimization problem, showing in particular that a minimizer can be found by solving a finite dimensional problem


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