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JMLR
2006
389views more  JMLR 2006»
15 years 6 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,...
NECO
2007
87views more  NECO 2007»
15 years 5 months ago
Reinforcement Learning State Estimator
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
Jun Morimoto, Kenji Doya
ICML
2003
IEEE
16 years 7 months ago
The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods
We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
Gavin Brown, Jeremy L. Wyatt
ESANN
2000
15 years 7 months ago
A neural network approach to adaptive pattern analysis - the deformable feature map
Abstract. In this paper, we presen t an algorithm that provides adaptive plasticity in function approximation problems: the deformable (feature) map (DM) algorithm. The DM approach...
Axel Wismüller, Frank Vietze, Dominik R. Ders...
ENGL
2007
109views more  ENGL 2007»
15 years 6 months ago
Using Neural Network for DJIA Stock Selection
—This paper presents methodologies to select equities based on soft-computing models which focus on applying fundamental analysis for equities screening. This paper compares the ...
Tong-Seng Quah