Learning, Regularization and Ill-Posed Inverse Problems

Volume: 17, Pages: 1145 - 1152
Published: Dec 1, 2004
Abstract
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 regularization theory. In this paper we provide a positive answer to both questions. Indeed,...
Paper Details
Title
Learning, Regularization and Ill-Posed Inverse Problems
Published Date
Dec 1, 2004
Volume
17
Pages
1145 - 1152
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