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UAI
1998
9 years 9 months ago
Learning From What You Don't Observe
The process of diagnosis involves learning about the state of a system from various observations of symptoms or findings about the system. Sophisticated Bayesian (and other) algor...
Mark A. Peot, Ross D. Shachter
ICCS
2007
Springer
9 years 10 months ago
Planet-in-a-Bottle: A Numerical Fluid-Laboratory System
Abstract. Humanity’s understanding of the Earth’s weather and climate depends critically on accurate forecasting and state-estimation technology. It is not clear how to build a...
Chris Hill, Bradley C. Kuszmaul, Charles E. Leiser...
AINA
2010
IEEE
10 years 1 months ago
Active Data Selection for Sensor Networks with Faults and Changepoints
Abstract—We describe a Bayesian formalism for the intelligent selection of observations from sensor networks that may intermittently undergo faults or changepoints. Such active d...
Michael A. Osborne, Roman Garnett, Stephen J. Robe...
AIIA
2005
Springer
10 years 1 months ago
Automata Slicing for Diagnosing Discrete-Event Systems with Partially Ordered Observations
Abstract. When dealing with real systems, it is unrealistic to suppose that observations can be totally ordered according to their emission dates. The partially ordered observation...
Alban Grastien, Marie-Odile Cordier, Christine Lar...
IJCNN
2006
IEEE
10 years 2 months ago
A Monte Carlo Sequential Estimation for Point Process Optimum Filtering
— Adaptive filtering is normally utilized to estimate system states or outputs from continuous valued observations, and it is of limited use when the observations are discrete e...
Yiwen Wang 0002, António R. C. Paiva, Jose ...
LOCA
2007
Springer
10 years 2 months ago
Inferring the Everyday Task Capabilities of Locations
Abstract. People rapidly learn the capabilities of a new location, without observing every service and product. Instead they map a few observations to familiar clusters of capabili...
Patricia Shanahan, William G. Griswold
ACIVS
2007
Springer
10 years 2 months ago
Joint Tracking and Segmentation of Objects Using Graph Cuts
This paper presents a new method to both track and segment objects in videos. It includes predictions and observations inside an energy function that is minimized with graph cuts. ...
Aurélie Bugeau, Patrick Pérez
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