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ISNN
2007
Springer
16 years 28 days ago
2007
Springer
Abstract. This paper investigates the construction of a wide class of singlehidden layer neural networks (SLNNs) with or without tunable parameters in the hidden nodes. It is a cha...
172
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GECCO
2006
Springer
15 years 10 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...
204
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ROCAI
2004
Springer
16 years 4 days ago
2004
Springer
We present an empirical comparison of the AUC performance of seven supervised learning methods: SVMs, neural nets, decision trees, k-nearest neighbor, bagged trees, boosted trees,...
180
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WAPCV
2004
Springer
16 years 4 days ago
2004
Springer
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
182
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ICANN
2010
Springer
15 years 7 months ago
2010
Springer
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...