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» Analysis of BPEL Data Dependencies
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103
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CIKM
1997
Springer
15 years 4 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
102
Voted
EWSN
2007
Springer
16 years 4 days ago
Removing Systematic Error in Node Localisation Using Scalable Data Fusion
Methods for node localisation in sensor networks usually rely upon the measurement of received strength, time-of-arrival, and/or angle-of-arrival of an incoming signal. In this pap...
Albert Krohn, Mike Hazas, Michael Beigl
111
Voted
ICCS
2005
Springer
15 years 6 months ago
Ensemble-Based Data Assimilation for Atmospheric Chemical Transport Models
The task of providing an optimal analysis of the state of the atmosphere requires the development of dynamic data-driven systems (d3 as) that efficiently integrate the observationa...
Adrian Sandu, Emil M. Constantinescu, Wenyuan Liao...
100
Voted
MA
2010
Springer
150views Communications» more  MA 2010»
14 years 7 months ago
Cokriging for spatial functional data
This work proposes to generalize the method of cokriging when data are spatially sampled curves. A spatial functional linear model is constructed including spatial dependencies be...
David Nerini, Pascal Monestiez, Claude Manté...
84
Voted
JCNS
2010
104views more  JCNS 2010»
14 years 11 months ago
A new look at state-space models for neural data
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...