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132
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GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 8 months ago
Genomic computing networks learn complex POMDPs
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...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
WAPCV
2004
Springer
15 years 10 months ago
Learning of Position-Invariant Object Representation Across Attention Shifts
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 ...
Muhua Li, James J. Clark
150
Voted
ICANN
2010
Springer
15 years 5 months ago
Deep Bottleneck Classifiers in Supervised Dimension Reduction
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Elina Parviainen
146
Voted
IJCINI
2008
107views more  IJCINI 2008»
15 years 5 months ago
Artificial Neural Networks that Classify Musical Chords
An artificial neural network was trained to classify musical chords into four categories--major, dominant seventh, minor, or diminished seventh--independent of musical key. After ...
Vanessa Yaremchuk, Michael R. W. Dawson
ECAL
2007
Springer
15 years 11 months ago
Developmental Neural Heterogeneity Through Coarse-Coding Regulation
Abstract. A coarse-coding regulatory model that facilitates neural heterogeneity through a morphogenetic process is presented. The model demonstrates cellular and tissue extensibil...
Jekanthan Thangavelautham, Gabriele M. T. D'Eleute...