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» Parametric Process Model Inference
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NIPS
1998
13 years 10 months ago
Learning to Estimate Scenes from Images
We seek the scene interpretation that best explains image data. For example, we may want to infer the projected velocities (scene) which best explain two consecutive image frames ...
William T. Freeman, Egon C. Pasztor
BMCBI
2006
96views more  BMCBI 2006»
13 years 8 months ago
Bayesian detection of periodic mRNA time profiles without use of training examples
Background: Detection of periodically expressed genes from microarray data without use of known periodic and non-periodic training examples is an important problem, e.g. for ident...
Claes R. Andersson, Anders Isaksson, Mats G. Gusta...
MONET
2007
95views more  MONET 2007»
13 years 8 months ago
A Pervasive Computing System for the Operating Room of the Future
We describe a prototype Context Aware Perioperative Information System to capture and interpret data in an operating room of the future. The captured data is used to construct the...
Sheetal K. Agarwal, Anupam Joshi, Timothy W. Finin...
PVLDB
2008
122views more  PVLDB 2008»
13 years 8 months ago
Exploiting shared correlations in probabilistic databases
There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources -from sensor data, experimental data, data fro...
Prithviraj Sen, Amol Deshpande, Lise Getoor
CONEXT
2010
ACM
13 years 6 months ago
NEVERMIND, the problem is already fixed: proactively detecting and troubleshooting customer DSL problems
Traditional DSL troubleshooting solutions are reactive, relying mainly on customers to report problems, and tend to be labor-intensive, time consuming, prone to incorrect resoluti...
Yu Jin, Nick G. Duffield, Alexandre Gerber, Patric...