Advanced Lectures on Machine Learning : ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures

Olivier Bousquet

ISBN 10: 3540231226 / ISBN 13: 9783540231226

Edité par Springer Berlin Heidelberg, 2004

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600.This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references.Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.

N° de réf. du vendeur 9783540231226

Détails bibliographiques

• Titre: Advanced Lectures on Machine Learning : ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures
• Éditeur: Springer Berlin Heidelberg
• Date de parution: 2004
• Langue: anglais
• ISBN à 10 chiffres: 3540231226
• ISBN à 13 chiffres: 9783540231226
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 15 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 15 millimètres de profondeur
• Poids: 394 grammes

A propos de ce titre

Synopsis

Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600.

This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references.

Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.