4079 search results - page 110 / 816 » Neural Networks |
110
Voted
GECCO
2005
Springer
15 years 9 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...
156
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NCA
1998
IEEE
15 years 3 months ago
1998
IEEE
This paper models information flow in a communication network. The network consists of nodes that communicate with each other, and information servers that have a predominantly o...
133
Voted
NN
2000
Springer
15 years 3 months ago
2000
Springer
In Lp-spaces with p [1, ) there exists a best approximation mapping to the set of functions computable by Heaviside perceptron networks with n hidden units; however for p (1, ) ...
129
Voted
TNN
1998
15 years 3 months ago
1998
—Recurrent neural networks processing symbolic strings can be regarded as adaptive neural parsers. Given a set of positive and negative examples, picked up from a given language,...
131
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IJON
2008
15 years 3 months ago
2008
The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...