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» On Generalization by Neural Networks
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TNN
1998
114views more  TNN 1998»
15 years 5 months ago
A new approach to artificial neural networks
: A novel approach to artificial neural networks is presented. The philosophy of this approach is based on two aspects: the design of task-specific networks, and a new neuron model...
Benedito Dias Baptista F. Filho, Eduardo Lobo Lust...
IDEAL
2005
Springer
15 years 11 months ago
Generating Predicate Rules from Neural Networks
Artificial neural networks play an important role for pattern recognition tasks. However, due to poor comprehensibility of the learned network, and the inability to represent expl...
Richi Nayak
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 11 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
APIN
2004
116views more  APIN 2004»
15 years 5 months ago
Neural Learning from Unbalanced Data
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
Yi Lu Murphey, Hong Guo, Lee A. Feldkamp
CSSE
2008
IEEE
16 years 2 days ago
Application of New Adaptive Higher Order Neural Networks in Data Mining
This paper introduces an adaptive Higher Order Neural Network (HONN) model and applies it in data mining such as simulating and forecasting government taxation revenues. The propo...
Shuxiang Xu, Ling Chen