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» On Generalization by Neural Networks
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TIT
2011
144views more  TIT 2011»
15 years 1 months ago
Network Generalized Hamming Weight
— In this paper, we extend the notion of generalized Hamming weight for classical linear block code to linear network codes by introducing the network generalized Hamming weight ...
Chi Kin Ngai, Raymond W. Yeung, Zhen Zhang
NN
2008
Springer
143views Neural Networks» more  NN 2008»
15 years 6 months ago
A batch ensemble approach to active learning with model selection
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
ESANN
2003
15 years 8 months ago
A new rule extraction algorithm based on interval arithmetic
In this paper we propose a new algorithm for rule extraction from a trained Multilayer Feedforward network. The algorithm is based on an interval arithmetic network inversion for p...
Carlos Hernández-Espinosa, Mercedes Fern&aa...
ICPR
2002
IEEE
16 years 7 months ago
Learning and Extracting Edges from Images by a Modified Hopfield Neural Network
This paper introduced a modified unsupervised Hopfield network that can learn the underlying process in an edge detection task from grey level images. After the learning phase, th...
Sylvain Chartier, Richard Lepage
ICANN
2007
Springer
16 years 23 days ago
SpikeStream: A Fast and Flexible Simulator of Spiking Neural Networks
SpikeStream is a new simulator of biologically structured spiking neural networks that can be used to edit, display and simulate up to 100,000 neurons. This simulator uses a combin...
David Gamez