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NIPS
1998
15 years 5 months ago
Computational Differences between Asymmetrical and Symmetrical Networks
Symmetrically connected recurrent networks have recently been used as models of a host of neural computations. However, biological neural networks have asymmetrical connections, at...
Zhaoping Li, Peter Dayan
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
15 years 10 months ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley
ACSC
2008
IEEE
15 years 6 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
PR
2007
165views more  PR 2007»
15 years 4 months ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch
159
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FLAIRS
2000
15 years 5 months ago
Systematic Treatment of Failures Using Multilayer Perceptrons
This paper discusses the empirical evaluation of improving generalization performance of neural networks by systematic treatment of training and test failures. As a result of syst...
Fadzilah Siraj, Derek Partridge