We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
Background: Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership...
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...
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...
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...