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NIPS
1998
13 years 9 months ago
Computational Differences between Asymmetrical and Symmetrical Networks
Symmetrically connected recurrent networks have recently been used as models of a host of neural computations. However, biological neural networks have asymmetrical connections, at...
Zhaoping Li, Peter Dayan
JMLR
2010
160views more  JMLR 2010»
13 years 2 months ago
Neural conditional random fields
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
Trinh Minh Tri Do, Thierry Artières
CCE
2008
13 years 8 months ago
Differential recurrent neural network based predictive control
An efficient algorithm to train general differential recurrent neural networks is proposed. The trained network can be directly used as the internal model of a predictive controll...
R. K. Al Seyab, Yi Cao
ICMLA
2010
13 years 6 months ago
Ensembles of Neural Networks for Robust Reinforcement Learning
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Alexander Hans, Steffen Udluft
JDCTA
2010
191views more  JDCTA 2010»
13 years 2 months ago
Improved Wavelet Neural Network Based on Hybrid Genetic Algorithm Applicationin on Fault Diagnosis of Railway Rolling Bearing
The method of improved wavelet transform neural network based on hybrid GA(genetic algorithm) is presented to diagnose rolling bearings faults in this paper. Genetic Artificial Ne...
Guoqiang Cai, Limin Jia, Jianwei Yang, Haibo Liu