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» On the Use of Evidence in Neural Networks
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IWANN
2001
Springer
15 years 6 months ago
A Penalization Criterion Based on Noise Behaviour for Model Selection
Complexity-penalization strategies are one way to decide on the most appropriate network size in order to address the trade-off between overfitted and underfitted models. In this p...
Joaquín Pizarro Junquera, Pedro Galindo Ria...
EVOW
2003
Springer
15 years 7 months ago
Comparison of AdaBoost and Genetic Programming for Combining Neural Networks for Drug Discovery
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cytochrome P450 activity by combining artificial neural networks (ANN). Pharmaceuti...
William B. Langdon, S. J. Barrett, Bernard F. Buxt...
ECAI
2010
Springer
15 years 3 months ago
Unsupervised Layer-Wise Model Selection in Deep Neural Networks
Abstract. Deep Neural Networks (DNN) propose a new and efficient ML architecture based on the layer-wise building of several representation layers. A critical issue for DNNs remain...
Ludovic Arnold, Hélène Paugam-Moisy,...
TNN
1998
111views more  TNN 1998»
15 years 1 months ago
Modular recurrent neural networks for Mandarin syllable recognition
Abstract—A new modular recurrent neural network (MRNN)based speech-recognition method that can recognize the entire vocabulary of 1280 highly confusable Mandarin syllables is pro...
Sin-Horng Chen, Yuan-Fu Liao
CORR
2011
Springer
212views Education» more  CORR 2011»
14 years 9 months ago
Combining Neural Networks for Skin Detection
Two types of combining strategies were evaluated namely combining skin features and combining skin classifiers. Several combining rules were applied where the outputs of the skin ...
Chelsia Amy Doukim, Jamal Ahmad Dargham, Ali Cheki...