Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2 - 14, 2003, Tübingen, Germany, August 4 - 16, 2003, Revised LecturesAuthor: Olivier Bousquet, Ulrike von Luxburg, Gunnar Rätsch Published by Springer Berlin Heidelberg ISBN: 978-3-540-23122-6 DOI: 10.1007/b100712Table 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