We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
This work elaborates on the connection between partial meet contractions and kernel contractions in belief change theory. We present a way to define incision functions (used in ker...
In this paper, we propose an agent-centric approach to resource description and selection in a multiagent information retrieval (IR). In the multiagent system, each agent learns f...
Sampling has become an important strategy for inference in belief networks. It can also be applied to the problem of selecting actions in influence diagrams. In this paper, we pre...
The ability to answer prediction questions is crucial to reasoning about physical systems. A prediction question poses a hypothetical scenario and asks for the resulting behavior ...