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ICANN
2009
Springer
14 years 1 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
KAIS
2000
106views more  KAIS 2000»
13 years 8 months ago
FANNC: A Fast Adaptive Neural Network Classifier
In this paper, a fast adaptive neural network classifier named FANNC is proposed. FANNC exploits the advantages of both adaptive resonance theory and field theory. It needs only on...
Zhi-Hua Zhou, Shifu Chen, Zhaoqian Chen
CVPR
1997
IEEE
14 years 11 months ago
Global Training of Document Processing Systems Using Graph Transformer Networks
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Léon Bottou, Yoshua Bengio, Yann LeCun
HIS
2008
13 years 10 months ago
Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
André L. D. Rossi, André C. P. L. F....
BMCBI
2006
109views more  BMCBI 2006»
13 years 9 months ago
GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease
Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and ...
Alison A. Motsinger, Stephen L. Lee, George Mellic...