Advanced Lectures on Machine Learning

Machine Learning Summer School 2002 Canberra, Australia, February 11–22, 2002 Revised Lectures

  • Shahar Mendelson
  • Alexander J. Smola
Book

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2600)

Also part of the Lecture Notes in Artificial Intelligence book sub series (volume 2600)

Table of contents

  1. Front Matter
    Pages I-X
  2. Shahar Mendelson
    Pages 1-40
  3. Bernhard Schölkopf, Alexander J. Smola
    Pages 41-64
  4. Alexander J. Smola, Bernhard Schölkopf
    Pages 65-117
  5. Ron Meir, Gunnar Rätsch
    Pages 118-183
  6. Markus Hegland
    Pages 226-234
  7. Jyrki Kivinen
    Pages 235-257
  8. Back Matter
    Pages 259-259

About this book

Introduction

Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11–22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at http://mlg. anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will ?nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.

Keywords

Algorithms Boosting algorithm kernel method learning learning theory machine learning reinforcement learning

Editors and affiliations

  • Shahar Mendelson
    • 1
  • Alexander J. Smola
    • 2
  1. 1.RSISEThe Australian National UniversityCanberraAustralia
  2. 2.Research School for Information Sciences and EngineeringThe Australian National UniversityCanberraAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-36434-X
  • Copyright Information Springer-Verlag Berlin Heidelberg 2003
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-00529-2
  • Online ISBN 978-3-540-36434-4
  • Series Print ISSN 0302-9743
  • About this book