Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
The memory resources required by network simulations can grow quadratically with size of the simulated network. In simulations that use routing tables at each node to perform perh...
George F. Riley, Mostafa H. Ammar, Richard Fujimot...
Practical applications of description logics (DLs) in knowledge-based systems have forced us to introduce the following features which are absent from existing DLs: • allowing a...
As high-speed networks make it easier to use distributed resources, it becomes increasingly common that applications and their data are not colocated. Users have traditionally add...
Ian T. Foster, David Kohr, Rakesh Krishnaiyer, Jac...
There is a growing interest in the integration of mechanized reasoning systems such as automated theorem provers, computer algebra systems, and model checkers. State-of-the-art re...