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IWANN
1999
Springer
13 years 9 months ago
A Modular Attractor Model of Semantic Access
This paper presents results from lesion experiments on a modular attractor neural network model of semantic access. Real picture data forms the basis of perceptual input to the mod...
William Power, Ray J. Frank, D. John Done, Neil Da...
APIN
1998
139views more  APIN 1998»
13 years 5 months ago
Evolutionary Learning of Modular Neural Networks with Genetic Programming
Evolutionary design of neural networks has shown a great potential as a powerful optimization tool. However, most evolutionary neural networks have not taken advantage of the fact ...
Sung-Bae Cho, Katsunori Shimohara
TNN
2008
177views more  TNN 2008»
13 years 5 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
PR
2007
118views more  PR 2007»
13 years 4 months ago
A cooperative constructive method for neural networks for pattern recognition
In this paper, we propose a new constructive method, based on cooperative coevolution, for designing automatically the structure of a neural network for classification. Our appro...
Nicolás García-Pedrajas, Domingo Ort...
CONTEXT
2001
Springer
13 years 10 months ago
A Connectionist-Symbolic Approach to Modeling Agent Behavior: Neural Networks Grouped by Contexts
A recent report by the National Research Council (NRC) declares neural networks “hold the most promise for providing powerful learning models”. While some researchers have expe...
Amy E. Henninger, Avelino J. Gonzalez, Michael Geo...