rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Advanced Lectures on Machine Learning
    sub title: Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures
  name:
    name part: Mendelson, Shahar.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Smola, Alexander J.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2003
    edition: 1st ed. 2003.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 266 p. online resource.
  abstract: 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.
  table of contents: A Few Notes on Statistical Learning Theory -- A Short Introduction to Learning with Kernels -- Bayesian Kernel Methods -- An Introduction to Boosting and Leveraging -- An Introduction to Reinforcement Learning Theory: Value Function Methods -- Learning Comprehensible Theories from Structured Data -- Algorithms for Association Rules -- Online Learning of Linear Classifiers.
  note: edited by Shahar Mendelson, Alexander J. Smola.
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computers
  subject:
    topic: Algorithms
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Science, Humanities and Social Sciences, multidisciplinary
  subject:
    topic: Computation by Abstract Devices
  subject:
    topic: Algorithm Analysis and Problem Complexity
  classification: Q334-342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Computer Science, 2600
  identifier: 9783540364344
  identifier: https://doi.org/10.1007/3-540-36434-X
  record info:
    record creation date: 121227
    record change date: 20191022161245.0
    record identifier: 978-3-540-36434-4