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A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
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Wu et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69ffcea4e4618ba4162d90b1 — DOI: https://doi.org/10.2307/1271368
Yuhai Wu
Vladimir Vapnik
Technometrics
Purdue University West Lafayette
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