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JMLR
2006
389views more  JMLR 2006»
13 years 7 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
TNN
2008
138views more  TNN 2008»
13 years 7 months ago
A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Zhenzhen Liu, Itamar Elhanany
ESANN
2003
13 years 9 months ago
Semi-automatic acquisition and labelling of image data using SOMs
Abstract. Application of neural networks for real world object recognition suffers from the need to acquire large quantities of labelled image data. We propose a solution that acq...
Gunther Heidemann, Axel Saalbach, Helge Ritter
IJCNN
2007
IEEE
14 years 1 months ago
Using Artificial Neural Networks and Feature Saliency Techniques for Improved Iris Segmentation
—One of the basic challenges to robust iris recognition is iris segmentation. This paper proposes the use of a feature saliency algorithm and an artificial neural network to perf...
Randy P. Broussard, Lauren R. Kennell, David L. So...
AAIM
2009
Springer
101views Algorithms» more  AAIM 2009»
14 years 2 months ago
Orca Reduction and ContrAction Graph Clustering
During the last years, a wide range of huge networks has been made available to researchers. The discovery of natural groups, a task called graph clustering, in such datasets is a ...
Daniel Delling, Robert Görke, Christian Schul...