We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
We describe a technique for automatically proving compiler optimizations sound, meaning that their transformations are always semantics-preserving. We first present a domainspeci...
Abstract--We present in this paper a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system (EPS), i....
Ole J. Mengshoel, Mark Chavira, Keith Cascio, Scot...
The most intuitive memory consistency model for shared-memory multi-threaded programming is sequential consistency (SC). However, current concurrent programming languages support ...
Daniel Marino, Abhayendra Singh, Todd D. Millstein...