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CORR
2011
Springer
174views Education» more  CORR 2011»
12 years 11 months ago
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
Yoshitaka Kameya, Taisuke Sato
BMCBI
2005
169views more  BMCBI 2005»
13 years 7 months ago
Genetic interaction motif finding by expectation maximization - a novel statistical model for inferring gene modules from synthe
Background: Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership...
Yan Qi 0003, Ping Ye, Joel S. Bader
IUI
2006
ACM
14 years 1 months ago
Who's asking for help?: a Bayesian approach to intelligent assistance
Automated software customization is drawing increasing attention as a means to help users deal with the scope, complexity, potential intrusiveness, and ever-changing nature of mod...
Bowen Hui, Craig Boutilier
IPMU
1992
Springer
13 years 11 months ago
Rule-Based Systems with Unreliable Conditions
This paper deals with the problem of inference under uncertain information. This is a generalization of a paper of Cardona et al. (1991a) where rules were not allowed to contain n...
L. Cardona, Jürg Kohlas, Paul-André Mo...
AAAI
2008
13 years 9 months ago
Hybrid Markov Logic Networks
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Jue Wang, Pedro Domingos