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AIPR
2005
IEEE
14 years 1 months ago
Hierarchical Bayesian Algorithm for Diffuse Optical Tomography
Diffuse Optical Tomography (DOT) poses a typical illposed inverse problem with limited number of measurements and inherently low spatial resolution. In this paper, we propose a hi...
Murat Guven, Birsen Yazici, Xavier Intes, Britton ...
IPSN
2011
Springer
12 years 11 months ago
Sensor networks for the detection and tracking of radiation and other threats in cities
This paper presents results from experiments, mathematical analysis, and simulations of a network of static and mobile sensors for detecting threats on city streets and in open ar...
Annie H. Liu, Julian J. Bunn, K. Mani Chandy
IJAR
2006
89views more  IJAR 2006»
13 years 7 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
UAI
2003
13 years 9 months ago
An Importance Sampling Algorithm Based on Evidence Pre-propagation
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
Changhe Yuan, Marek J. Druzdzel
AAAI
2008
13 years 9 months ago
Bounding the False Discovery Rate in Local Bayesian Network Learning
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
Ioannis Tsamardinos, Laura E. Brown