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Principles of Nonparametric Learning de Laszlo Györfi

Principles of Nonparametric Learning: CISM International Centre for Mechanical Sciences, cartea 434

Editat de Laszlo Györfi
en Limba Engleză Paperback – 30 iul 2002
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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Specificații

ISBN-13: 9783211836880
ISBN-10: 3211836888
Pagini: 348
Ilustrații: V, 335 p.
Dimensiuni: 170 x 244 x 19 mm
Greutate: 0.6 kg
Ediția:2002
Editura: Springer
Colecția CISM International Centre for Mechanical Sciences
Seria CISM International Centre for Mechanical Sciences

Locul publicării:Vienna, Austria

Public țintă

Research

Cuprins

Pattern classification and learning theory (G. Lugosi).- Nonparametric regression estimation (L. Györfi, M. Kohler).- Universal prediction (N. Cesa-Bianchi).- Learning-theoretic methods in vector quantization (T. Linder).- Distribution and density estimation (L. Devroye, L. Györfi).- Programming applied to model identification (M. Sebag)