Computational Learning Theory and Natural Learning Systems, Vol. I: Constraints and Prospects
Language: English
Published by A Bradford Book, 1994
- Softcover
- New
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Seller Inventory # MA-144A1-0262581264
- Title
- Computational Learning Theory and Natural Learning Systems, Vol. I: Constraints and Prospects
- Author
- Drastal, George A.; Hanson, Stephen Jose
- Publisher
- A Bradford Book
- Publication year
- 1994
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0262581264
- ISBN 13
- 9780262581264
In all, nineteen chapters address questions such as, What is a natural system? How should learning systems gain from prior knowledge? If prior knowledge is important, how can we quantify how important? What makes a learning problem hard? How are neural networks and symbolic machine learning approaches similar? Is there a fundamental difference in the kind of task a neural network can easily solve as opposed to those a symbolic algorithm can easily solve?
Stephen J. Hanson heads the Learning Systems Department at Siemens Corporate Research and is a Visiting Member of the Research Staff and Research Collaborator at the Cognitive Science Laboratory at Princeton University. George A. Drastal is Senior Research Scientist at Siemens Corporate Research. Ronald J. Rivest is Professor of Computer Science and Associate Director of the Laboratory for Computer Science at the Massachusetts Institute of Technology.
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