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» Introduction to Causal Inference
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UAI
2004
14 years 11 months ago
Bayesian Biosurveillance of Disease Outbreaks
Early, reliable detection of disease outbreaks is a critical problem today. This paper reports an investigation of the use of causal Bayesian networks to model spatio-temporal pat...
Gregory F. Cooper, Denver Dash, John Levander, Wen...
SOSP
2003
ACM
15 years 6 months ago
Performance debugging for distributed systems of black boxes
Many interesting large-scale systems are distributed systems of multiple communicating components. Such systems can be very hard to debug, especially when they exhibit poor perfor...
Marcos Kawazoe Aguilera, Jeffrey C. Mogul, Janet L...
BMCBI
2010
172views more  BMCBI 2010»
14 years 9 months ago
Comparison of evolutionary algorithms in gene regulatory network model inference
Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineeri...
Alina Sîrbu, Heather J. Ruskin, Martin Crane
CP
2005
Springer
15 years 3 months ago
Search and Inference in AI Planning
While Planning has been a key area in Artificial Intelligence since its beginnings, significant changes have occurred in the last decade as a result of new ideas and a more estab...
Hector Geffner
CVPR
2009
IEEE
16 years 4 months ago
Illumination and Spatially Varying Specular Reflectance from a Single View
Estimating the illumination and the reflectance properties of an object surface from a sparse set of images is an important but inherently ill-posed problem. The problem becomes...
Kenji Hara (Kyushu University), Ko Nishino (Drexel...