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» A Minimax Method for Learning Functional Networks
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IPSN
2010
Springer
14 years 2 months ago
Bayesian optimization for sensor set selection
We consider the problem of selecting an optimal set of sensors, as determined, for example, by the predictive accuracy of the resulting sensor network. Given an underlying metric ...
Roman Garnett, Michael A. Osborne, Stephen J. Robe...
AES
2008
Springer
133views Cryptology» more  AES 2008»
13 years 7 months ago
Alternative neural networks to estimate the scour below spillways
Artificial neural networks (ANN's) are associated with difficulties like lack of success in a given problem and unpredictable level of accuracy that could be achieved. In eve...
H. Md. Azamathulla, M. C. Deo, P. B. Deolalikar
BMCBI
2008
98views more  BMCBI 2008»
13 years 7 months ago
GBNet: Deciphering regulatory rules in the co-regulated genes using a Gibbs sampler enhanced Bayesian network approach
Background: Combinatorial regulation of transcription factors (TFs) is important in determining the complex gene expression patterns particularly in higher organisms. Deciphering ...
Li Shen, Jie Liu, Wei Wang
IJON
2002
185views more  IJON 2002»
13 years 7 months ago
An image retrieval system by impression words and specific object names - IRIS
Image content analysis has become an important issue in multimedia processing. Region-based image retrieval systems attempt to reduce the gap between high-level semantics and low-l...
Kazuhiro Kuroda, Masafumi Hagiwara
BMCBI
2006
202views more  BMCBI 2006»
13 years 7 months ago
Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks
Background: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the sea...
David J. Reiss, Nitin S. Baliga, Richard Bonneau