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CVPR
2008
IEEE
14 years 10 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
CORR
2011
Springer
202views Education» more  CORR 2011»
13 years 2 months ago
Network Estimation and Packet Delivery Prediction for Control over Wireless Mesh Networks
: Much of the current theory of networked control systems uses simple point-to-point communiodels as an abstraction of the underlying network. As a result, the controller has very ...
Phoebus Chen, Chithrupa Ramesh, Karl Henrik Johans...
AI
2002
Springer
13 years 7 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
IPPS
2008
IEEE
14 years 2 months ago
On utilization of contributory storage in desktop grids
Modern desktop grid environments and shared computing platforms have popularized the use of contributory resources, such as desktop computers, as computing substrates for a variet...
Chreston Miller, Ali Raza Butt, Patrick Butler
IJON
2010
138views more  IJON 2010»
13 years 6 months ago
A dynamic Bayesian network to represent discrete duration models
Originally devoted to specific applications such as biology, medicine and demography, duration models are now widely used in economy, finance or reliability. Recent works in var...
Roland Donat, Philippe Leray, Laurent Bouillaut, P...