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Principles of Nonparametric Learning

Principles of Nonparametric Learning Computer Science

Principles of Nonparametric Learning

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Description
The book provides 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. The book is mainly addressed to postgraduates in engineering, mathematics, computer science, and researchers in universities and research institutions.
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
348
Release Date:
2002-07-30
Publication Date:
2002-07-30
Publisher:
Springer
Languages:
Original: English
ISBN10:
3211836888
ISBN13:
9783211836880
GPSR Manufacturer Reference:
Weight:
601 g
Height:
170 cm
Width:
244 cm
Thickness:
19 cm
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