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» Two Algorithms for Inducing Causal Models from Data
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DMSN
2008
ACM
14 years 11 months ago
Probabilistic processing of interval-valued sensor data
When dealing with sensors with different time resolutions, it is desirable to model a sensor reading as pertaining to a time interval rather than a unit of time. We introduce two ...
Sander Evers, Maarten M. Fokkinga, Peter M. G. Ape...
CEC
2003
IEEE
15 years 3 months ago
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization
Neural networks and the Kriging method are compared for constructing £tness approximation models in evolutionary optimization algorithms. The two models are applied in an identica...
Lars Willmes, Thomas Bäck, Yaochu Jin, Bernha...
CVPR
2005
IEEE
15 years 12 months ago
A Statistical Field Model for Pedestrian Detection
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Ying Wu, Ting Yu, Gang Hua
MICCAI
2009
Springer
15 years 11 months ago
Personalized Modeling and Assessment of the Aortic-Mitral Coupling from 4D TEE and CT
The anatomy, function and hemodynamics of the aortic and mitral valves are known to be strongly interconnected. An integrated quantitative and visual assessment of the aortic-mitra...
Razvan Ioan Ionasec, Ingmar Voigt, Bogdan George...
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
15 years 10 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger