Principles of Nonparametric Learning

By: Laszlo Györfi

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eText | 4 May 2014 | Edition Number 1

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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.