Principles of Nonparametric Learning
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Product Details
Brand
Springer Nature
Manufacturer
N/A
Part Number
0
GTIN
9783211836880
Condition
New
Product 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.
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