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» The Complexity of Probabilistic EL
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FUIN
2008
108views more  FUIN 2008»
13 years 6 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
ICIP
2007
IEEE
14 years 9 months ago
Hierarchical Feature Fusion for Visual Tracking
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from clutte...
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavr...
ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
14 years 1 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
NIPS
2008
13 years 9 months ago
A mixture model for the evolution of gene expression in non-homogeneous datasets
We address the challenge of assessing conservation of gene expression in complex, non-homogeneous datasets. Recent studies have demonstrated the success of probabilistic models in...
Gerald Quon, Yee Whye Teh, Esther Chan, Timothy R....
MOC
2002
131views more  MOC 2002»
13 years 7 months ago
Some baby-step giant-step algorithms for the low hamming weight discrete logarithm problem
In this paper, we present several baby-step giant-step algorithms for the low hamming weight discrete logarithm problem. In this version of the discrete log problem, we are require...
Douglas R. Stinson