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Principles of Nonparametric Learning

Principles of Nonparametric Learning by Laszlo Györfi
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This volume provides a systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and estimates, such as pattern recognition, nonparametric regression estimation, universal prediction, vector quantization, distribution and density estimation, and genetic programming.

Springer Vienna; May 2014
344 pages; ISBN 9783709125687
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Title: Principles of Nonparametric Learning
Author: Laszlo Györfi
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