135 search results - page 4 / 27 » Solving the Ill-Conditioning in Neural Network Learning |
GECCO
2006
Springer
15 years 5 months ago
2006
Springer
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
GECCO
2005
Springer
15 years 7 months ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
122
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ICANN
2009
Springer
15 years 6 months ago
2009
Springer
Learning to solve small instances of a problem should help in solving large instances. Unfortunately, most neural network architectures do not exhibit this form of scalability. Our...
140
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ICANN
2009
Springer
14 years 11 months ago
2009
Springer
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
133
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ITS
2004
Springer
15 years 6 months ago
2004
Springer
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...