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Advanced Lectures on Machine Learning




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 T{\"u}bingen, 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.

Author(s): Bousquet, O. and von Luxburg, U. and Rätsch, G.
Journal: ML Summer Schools 2003
Volume: LNAI 3176
Pages: 240
Year: 2004
Month: September
Day: 0
Publisher: Springer

Department(s): Empirical Inference
Bibtex Type: Proceedings (proceedings)

Address: Berlin, Germany
Digital: 0
Event Name: ML Summer Schools 2003
Event Place: Canberra, Australia
ISBN: 978-3-540-23122-6
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: Web


  title = {Advanced Lectures on Machine Learning},
  author = {Bousquet, O. and von Luxburg, U. and R{\"a}tsch, G.},
  journal = {ML Summer Schools 2003},
  volume = {LNAI 3176},
  pages = {240},
  publisher = {Springer},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Berlin, Germany},
  month = sep,
  year = {2004},
  month_numeric = {9}