The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there...
Defeasible logic is a system of reasoning in which rules have exceptions, and when rules conflict, the one that applies most specifically to the situation wins out. This paper repo...
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a ...
—Statistical information extraction (IE) programs are increasingly used to build real-world IE systems such as Alibaba, CiteSeer, Kylin, and YAGO. Current statistical IE approach...