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The Springer International Series in Engineering and Computer Science

Change of Representation and Inductive Bias

Editors: Benjamin, D. Paul (Ed.)

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About this book

Change of Representation and Inductive Bias One of the most important emerging concerns of machine learning researchers is the dependence of their learning programs on the underlying representations, especially on the languages used to describe hypotheses. The effectiveness of learning algorithms is very sensitive to this choice of language; choosing too large a language permits too many possible hypotheses for a program to consider, precluding effective learning, but choosing too small a language can prohibit a program from being able to find acceptable hypotheses. This dependence is not just a pitfall, however; it is also an opportunity. The work of Saul Amarel over the past two decades has demonstrated the effectiveness of representational shift as a problem-solving technique. An increasing number of machine learning researchers are building programs that learn to alter their language to improve their effectiveness. At the Fourth Machine Learning Workshop held in June, 1987, at the University of California at Irvine, it became clear that the both the machine learning community and the number of topics it addresses had grown so large that the representation issue could not be discussed in sufficient depth. A number of attendees were particularly interested in the related topics of constructive induction, problem reformulation, representation selection, and multiple levels of abstraction. Rob Holte, Larry Rendell, and I decided to hold a workshop in 1988 to discuss these topics. To keep this workshop small, we decided that participation be by invitation only.

Table of contents (18 chapters)

Table of contents (18 chapters)

Buy this book

eBook $139.00
price for USA in USD (gross)
  • ISBN 978-1-4613-1523-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $214.00
price for USA in USD
  • ISBN 978-0-7923-9055-8
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
Softcover $179.99
price for USA in USD
  • ISBN 978-1-4612-8817-6
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Change of Representation and Inductive Bias
Editors
  • D. Paul Benjamin
Series Title
The Springer International Series in Engineering and Computer Science
Series Volume
87
Copyright
1990
Publisher
Springer US
Copyright Holder
Kluwer Academic Publishers
eBook ISBN
978-1-4613-1523-0
DOI
10.1007/978-1-4613-1523-0
Hardcover ISBN
978-0-7923-9055-8
Softcover ISBN
978-1-4612-8817-6
Series ISSN
0893-3405
Edition Number
1
Number of Pages
XII, 356
Topics

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