Advanced Lectures on Machine Learning 2003

Olivier Bousquet, Ulrike von Luxburg, Gunnar Rätsch (Eds.): Advanced Lectures on Machine Learning, ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures. Lecture Notes in Computer Science 3176 Springer 2004, ISBN 3-540-23122-6

Elad Yom-Tov:
An Introduction to Pattern Classification. 1-20
Christopher J. C. Burges:
Some Notes on Applied Mathematics for Machine Learning. 21-40
Michael E. Tipping:
Bayesian Inference: An Introduction to Principles and Practice in Machine Learning. 41-62
Carl Edward Rasmussen:
Gaussian Processes in Machine Learning. 63-71
Zoubin Ghahramani:
Unsupervised Learning. 72-112
Christophe Andrieu:
Monte Carlo Methods for Absolute Beginners. 113-145
Léon Bottou:
Stochastic Learning. 146-168
Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi:
Introduction to Statistical Learning Theory. 169-207
Stéphane Boucheron, Gábor Lugosi, Olivier Bousquet:
Concentration Inequalities. 208-240

Last update Mon May 21 02:19:02 2012 CET by the DBLP Team —

Data released under the ODC-BY 1.0 license — See also our legal information page