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ICANN
2010
Springer
15 years 6 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
IJCINI
2008
107views more  IJCINI 2008»
15 years 6 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
16 years 21 days 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...
EPIA
2003
Springer
15 years 11 months ago
Evolutionary Neuroestimation of Fitness Functions
Abstract. One of the most influential factors in the quality of the solutions found by an evolutionary algorithm is the appropriateness of the fitness function. Specifically in ...
Jesús S. Aguilar-Ruiz, Daniel Mateos, Domin...
NN
2008
Springer
15 years 6 months ago
Two k-winners-take-all networks with discontinuous activation functions
This paper presents two k-winners-take-all (k-WTA) networks with discontinuous activation functions. The k-WTA operation is first converted equivalently into linear and quadratic ...
Qingshan Liu, Jun Wang