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85
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PRL
1998
132views more  PRL 1998»
15 years 10 days ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal
84
Voted
NN
1998
Springer
156views Neural Networks» more  NN 1998»
15 years 11 days ago
Automatic early stopping using cross validation: quantifying the criteria
Cross validation can be used to detect when over tting starts during supervised training of a neural network; training is then stopped before convergence to avoid the overtting  ...
Lutz Prechelt
ICANN
2010
Springer
15 years 1 months ago
Using Reinforcement Learning to Guide the Development of Self-organised Feature Maps for Visual Orienting
We present a biologically inspired neural network model of visual orienting (using saccadic eye movements) in which targets are preferentially selected according to their reward va...
Kevin Brohan, Kevin N. Gurney, Piotr Dudek
100
Voted
CONNECTION
2004
92views more  CONNECTION 2004»
15 years 16 days ago
High capacity associative memories and connection constraints
: High capacity associative neural networks can be built from networks of perceptrons, trained using simple perceptron training. Such networks perform much better than those traine...
Neil Davey, Rod Adams
ANNPR
2006
Springer
15 years 4 months ago
Support Vector Regression Using Mahalanobis Kernels
Abstract. In our previous work we have shown that Mahalanobis kernels are useful for support vector classifiers both from generalization ability and model selection speed. In this ...
Yuya Kamada, Shigeo Abe