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Proceedings of the 1993 Connectionist Models Summer School

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advanced neural computation research
Back Propagation
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Codebook Vectors
computational neuroscience
Connectionist Model
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function
Generalization Error
hidden
Hidden Units
information
Input Pattern
iterated
Iterated Function Systems
National Academy
neural
Neural Net
Ocular Dominance
Ocular Dominance Columns
Output Units
Past Tenses
phonological representation modeling
Place Cell Activity
processing
Recurrent Networks
Recurrent Neural Network
recurrent neural networks
Reinforcement Learning Techniques
Rule Extraction
Rule Extraction Methods
self-organizing maps
Set Error
Stochastic Gradient Descent
symbolic processing models
systems
Training Error
Training Set
Training Set Error
Unit Si
units
unsupervised learning algorithms
vectors
weight

Product details

  • ISBN 9780805815900
  • Weight: 940g
  • Dimensions: 219 x 276mm
  • Publication Date: 01 Nov 1993
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

The result of the 1993 Connectionist Models Summer School, the papers in this volume exemplify the tremendous breadth and depth of research underway in the field of neural networks. Although the slant of the summer school has always leaned toward cognitive science and artificial intelligence, the diverse scientific backgrounds and research interests of accepted students and invited faculty reflect the broad spectrum of areas contributing to neural networks, including artificial intelligence, cognitive science, computer science, engineering, mathematics, neuroscience, and physics. Providing an accurate picture of the state of the art in this fast-moving field, the proceedings of this intense two-week program of lectures, workshops, and informal discussions contains timely and high-quality work by the best and the brightest in the neural networks field.
About
Mozer, Michael C.; Smolensky, Paul; Touretzky, David S.; Elman, Jeffrey L.; Weigend, Andreas S.