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» A theoretical framework for multiple neural network systems
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ISPA
2004
Springer
14 years 2 months ago
Cayley DHTs - A Group-Theoretic Framework for Analyzing DHTs Based on Cayley Graphs
Static DHT topologies influence important features of such DHTs such as scalability, communication load balancing, routing efficiency and fault tolerance. Nevertheless, it is co...
Changtao Qu, Wolfgang Nejdl, Matthias Kriesell
NN
2008
Springer
158views Neural Networks» more  NN 2008»
13 years 8 months ago
Optimal wide-area monitoring and nonlinear adaptive coordinating neurocontrol of a power system with wind power integration and
Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area coordinating neurocont...
Wei Qiao, Ganesh K. Venayagamoorthy, Ronald G. Har...
TIT
2002
89views more  TIT 2002»
13 years 8 months ago
Comparison of worst case errors in linear and neural network approximation
Sets of multivariable functions are described for which worst case errors in linear approximation are larger than those in approximation by neural networks. A theoretical framework...
Vera Kurková, Marcello Sanguineti
ICANN
2011
Springer
13 years 7 days ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes
IJCNN
2008
IEEE
14 years 3 months ago
On the sample mean of graphs
— We present an analytic and geometric view of the sample mean of graphs. The theoretical framework yields efficient subgradient methods for approximating a structural mean and ...
Brijnesh J. Jain, Klaus Obermayer