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FLAIRS
2004
13 years 10 months ago
Invariance of MLP Training to Input Feature De-correlation
In the neural network literature, input feature de-correlation is often referred as one pre-processing technique used to improve the MLP training speed. However, in this paper, we...
Changhua Yu, Michael T. Manry, Jiang Li
ICONIP
2010
13 years 7 months ago
Learning Shapes Bifurcations of Neural Dynamics upon External Stimuli
Memory is often considered to be embedded into one of the attractors in neural dynamical systems, which provides an appropriate output depending on the initial state specified by ...
Tomoki Kurikawa, Kunihiko Kaneko
IWANN
1999
Springer
14 years 1 months ago
A Modular Attractor Model of Semantic Access
This paper presents results from lesion experiments on a modular attractor neural network model of semantic access. Real picture data forms the basis of perceptual input to the mod...
William Power, Ray J. Frank, D. John Done, Neil Da...
CEC
2008
IEEE
14 years 3 months ago
Learning what to ignore: Memetic climbing in topology and weight space
— We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning ...
Julian Togelius, Faustino J. Gomez, Jürgen Sc...
ICANN
2007
Springer
14 years 3 months ago
Generalized Softmax Networks for Non-linear Component Extraction
Abstract. We develop a probabilistic interpretation of non-linear component extraction in neural networks that activate their hidden units according to a softmaxlike mechanism. On ...
Jörg Lücke, Maneesh Sahani