CISM International Centre for Mechanical Sciences

Györfi, Laszlo

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.

Details

Published by: Springer

Publication Date: 2002-07-30

Format: Paperback

ISBN-13: 9783211836880

DOI: 10.1007/978-3-7091-2568-7

Dimensions: 244cm x170cm

Pages: 335