Principles of Nonparametric Learning

Principles of Nonparametric Learning

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.


Author
Publisher Springer
Release Date
ISBN 3709125685
Pages 335 pages
Principles of Nonparametric Learning
Language: en
Pages: 335
Authors: Laszlo Györfi
Categories: Technology & Engineering
Type: BOOK - Published: 2014-05-04 - Publisher: Springer

This volume provides a systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and esti
An Elementary Introduction to Statistical Learning Theory
Language: en
Pages: 288
Authors: Sanjeev Kulkarni
Categories: Mathematics
Type: BOOK - Published: 2011-06-09 - Publisher: John Wiley & Sons

A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading resea
Learning Theory
Language: en
Pages: 656
Authors: Gábor Lugosi
Categories: Computers
Type: BOOK - Published: 2006-06-12 - Publisher: Springer Science & Business Media

This book constitutes the refereed proceedings of the 19th Annual Conference on Learning Theory, COLT 2006, held in Pittsburgh, Pennsylvania, USA in June 2006.
Advanced Lectures on Machine Learning
Language: en
Pages: 246
Authors: Olivier Bousquet
Categories: Computers
Type: BOOK - Published: 2011-03-22 - Publisher: Springer

Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To s
A Distribution-Free Theory of Nonparametric Regression
Language: en
Pages: 650
Authors: László Györfi
Categories: Mathematics
Type: BOOK - Published: 2006-04-18 - Publisher: Springer Science & Business Media

This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distr
Principles and Theory for Data Mining and Machine Learning
Language: en
Pages: 786
Authors: Bertrand Clarke
Categories: Computers
Type: BOOK - Published: 2009-07-21 - Publisher: Springer Science & Business Media

Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Co
Advanced Lectures on Machine Learning
Language: en
Pages:
Authors:
Categories: Machine learning
Type: BOOK - Published: 2003 - Publisher:

The Principles of Deep Learning Theory
Language: en
Pages: 472
Authors: Daniel A. Roberts
Categories: Computers
Type: BOOK - Published: 2022-05-26 - Publisher: Cambridge University Press

This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Greedy Approximation
Language: en
Pages:
Authors: Vladimir Temlyakov
Categories: Computers
Type: BOOK - Published: 2011-09-08 - Publisher: Cambridge University Press

This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numeri
From Data and Information Analysis to Knowledge Engineering
Language: en
Pages: 788
Authors: Myra Spiliopoulou
Categories: Language Arts & Disciplines
Type: BOOK - Published: 2006-02-09 - Publisher: Springer Science & Business Media

This volume collects revised versions of papers presented at the 29th Annual Conference of the Gesellschaft für Klassifikation, the German Classification Socie