Umberto De Giovannini

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Many works related learning from examples to regularization techniques for inverse problems, emphasizing the strong algorithmic and conceptual analogy of certain learning algorithms with regu-larization algorithms. In particular it is well known that regularization schemes such as Tikhonov regularization can be effectively used in the context of learning(More)
Many works have shown that strong connections relate learning from examples to regularization techniques for ill-posed inverse problems. Nevertheless by now there was no formal evidence neither that learning from examples could be seen as an inverse problem nor that theoretical results in learning theory could be independently derived using tools from(More)
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