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» On the Use of Evidence in Neural Networks
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IEEEARES
2006
IEEE
16 years 20 days 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
ECSQARU
1995
Springer
15 years 10 months ago
Parametric Structure of Probabilities in Bayesian Networks
The paper presents a method for uncertainty propagation in Bayesian networks in symbolic, as opposed to numeric, form. The algebraic structure of probabilities is characterized. Th...
Enrique Castillo, José Manuel Gutiér...
WWW
2005
ACM
16 years 7 months ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a ch...
Yan-Shi Dong, Ke-Song Han
ARTCOM
2009
IEEE
16 years 1 months ago
Image Segmentation - A Survey of Soft Computing Approaches
—Soft Computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. Soft computing techniques have found w...
N. Senthilkumaran, R. Rajesh
CANDC
2009
ACM
16 years 1 months ago
A sub-symbolic model of the cognitive processes of re-representation and insight
We present a sub-symbolic computational model for effecting knowledge re-representation and insight. Given a set of data, manifold learning is used to automatically organize the d...
Dan Ventura