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CVPR
2008
IEEE
14 years 9 months ago
Learning Bayesian Networks with qualitative constraints
Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Yan Tong, Qiang Ji
ICTAI
2009
IEEE
14 years 2 months ago
Probabilistic Neural Logic Network Learning: Taking Cues from Neuro-Cognitive Processes
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
Henry Wai Kit Chia, Chew Lim Tan, Sam Yuan Sung
IEEEARES
2006
IEEE
14 years 1 months ago
Bayesian Networks Implementation of the Dempster Shafer Theory to Model Reliability Uncertainty
In many reliability studies based on data, reliability engineers face incompleteness and incoherency problems in the data. Probabilistic tools badly handle these kinds of problems...
Christophe Simon, Philippe Weber
AIME
2007
Springer
13 years 11 months ago
Using Temporal Context-Specific Independence Information in the Exploratory Analysis of Disease Processes
Abstract. Disease processes in patients are temporal in nature and involve uncertainty. It is necessary to gain insight into these processes when aiming at improving the diagnosis,...
Stefan Visscher, Peter J. F. Lucas, Ildikó ...
IIWAS
2008
13 years 9 months ago
On-the-fly collaboration in distributed systems through service semantic overlay
In the recent years distributed architectures and P2P technology have been adopted to better support effective collaboration among networked organizations. According to the P2P pa...
Devis Bianchini, Valeria De Antonellis, Michele Me...