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» A theoretical framework for multiple neural network systems
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ESANN
2008
13 years 9 months ago
A multiple testing procedure for input variable selection in neural networks
In this paper a novel procedure to select the input nodes in neural network modeling is presented and discussed. The approach is developed in a multiple testing framework and so it...
Michele La Rocca, Cira Perna
ICPR
2000
IEEE
14 years 4 hour ago
A Theoretical Framework for Dynamic Classifier Selection
At present, the common operation mechanism of multiple classifier systems is the combination of classifier outputs. Recently, some researchers pointed out the potentialities of ...
Giorgio Giacinto, Fabio Roli
AAAI
2012
11 years 10 months ago
Computing Game-Theoretic Solutions and Applications to Security
The multiagent systems community has adopted game theory as a framework for the design of systems of multiple self-interested agents. For this to be effective, efficient algorith...
Vincent Conitzer
IJCNN
2000
IEEE
13 years 12 months ago
Input Window Size and Neural Network Predictors
Neural Network approaches to time series prediction are briefly discussed, and the need to specify an appropriately sized input window identified. Relevant theoretical results fro...
Ray J. Frank, Neil Davey, S. P. Hunt
AIA
2006
13 years 9 months ago
Recurrent and Concurrent Neural Networks for Objects Recognition
A system based on a neural network framework is considered. We used two neural networks, an Elman network [1][2] and a Kohonen (concurrent) network [3], for a categorization task....
Federico Cecconi, Marco Campenní