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» Bayesian learning of measurement and structural models
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ESWA
2006
103views more  ESWA 2006»
14 years 12 months ago
Model gene network by semi-fixed Bayesian network
Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, and protein or RNA transport. Thus, le...
Tie-Fei Liu, Wing-Kin Sung, Ankush Mittal
CVPR
2004
IEEE
16 years 1 months ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black
FUIN
2008
108views more  FUIN 2008»
14 years 10 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
AI
2002
Springer
14 years 11 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
CIKM
2009
Springer
15 years 6 months ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang