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NIPS
2008
15 years 8 months ago
Learning Bounded Treewidth Bayesian Networks
With the increased availability of data for complex domains, it is desirable to learn Bayesian network structures that are sufficiently expressive for generalization while at the ...
Gal Elidan, Stephen Gould
ACSC
2005
IEEE
16 years 14 days ago
Simulating Network Robustness for Critical Infrastructure Networks
We examine the robustness of critical infrastructure networks in the face of terrorist attack, using a simulation experiment that incorporates link capacity; and an extension of d...
Anthony H. Dekker
178
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ISNN
2005
Springer
16 years 10 days ago
A Novel Solid Neuron-Network Chip Based on Both Biological and Artificial Neural Network Theories
Built on the theories of biological neural network, artificial neural network methods have shown many significant advantages. However, the memory space in an artificial neural chip...
Zihong Liu, Zhihua Wang, Guolin Li, Zhiping Yu
IJCNN
2006
IEEE
16 years 26 days ago
Complex Systems Modeling Using Scale-Free Highly-Clustered Echo State Network
— Inspired by the universal laws governing different kinds of complex networks, we propose a scale-free highlyclustered echo state network (SHESN). Different from echo state netw...
Zhidong Deng, Yi Zhang
IJCNN
2006
IEEE
16 years 26 days ago
High-speed Bi-directional Function Approximation using Plausible Neural Networks
— This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mut...
Kuo-Chen Li, Dar-Jen Chang, Yuan Yan Chen