Advanced lectures on machine learning : ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003 [and] Tübingen, Germany, August 4-16, 2003 : revised lectures

Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2 - 14, 2003, Tübingen, Germany, August 4 - 16, 2003, Revised Lectures
Author: Olivier Bousquet, Ulrike von Luxburg, Gunnar Rätsch
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-23122-6
DOI: 10.1007/b100712

Table of Contents:

• An Introduction to Pattern Classification
• Some Notes on Applied Mathematics for Machine Learning
• Bayesian Inference: An Introduction to Principles and Practice in Machine Learning
• Gaussian Processes in Machine Learning
• Unsupervised Learning
• Monte Carlo Methods for Absolute Beginners
• Stochastic Learning
• Introduction to Statistical Learning Theory
• Concentration Inequalities

Includes bibliographical references and index
An introduction to pattern classification / Elad Yom-Tov -- Some notes on applied mathematics for machine learning / Christopher J.C. Burges -- Bayesian inference: an introduction to principles and practice in machine learning / Michael E. Tipping -- Gaussian processes in machine learning / Carl Edward Rasmussen -- Unsupervised learning / Zoubin Ghahramani -- Monte Carlo methods for absolute beginners / Christophe Andrieu -- Stochastic learning / Leon Bottou -- Introduction to statistical learning theory / Olivier Bousquet, Stephane Boucheron, Gabor Lugosi -- Concentration inequalities / Stephane Boucheron, Gabor Lugosi, Olivier Bousquet