We consider two-dimensional spatial databases defined in terms of polynomial inequalities and focus on the potential of programming languages for such databases to express queries...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
In various application domains there is a desire to compare process models, e.g., to relate an organization-specific process model to a reference model, to find a web service match...
Wil M. P. van der Aalst, Ana Karla A. de Medeiros,...
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
This paper argues for an implicitly parallel programming model for many-core microprocessors, and provides initial technical approaches towards this goal. In an implicitly paralle...
Wen-mei W. Hwu, Shane Ryoo, Sain-Zee Ueng, John H....