Abstract-- Scheduling problems are already difficult on traditional parallel machines, and they become extremely challenging on heterogeneous clusters. In this paper we deal with t...
Anne Benoit, Loris Marchal, Jean-Francois Pineau, ...
Probabilistic inference in graphical models is a prevalent task in statistics and artificial intelligence. The ability to perform this inference task efficiently is critical in l...
Open Information Extraction extracts relations from text without requiring a pre-specified domain or vocabulary. While existing techniques have used only shallow syntactic featur...
Janara Christensen, Mausam, Stephen Soderland, Ore...
Belief propagation (BP) is an effective algorithm for solving energy minimization problems in computer vision. However, it requires enormous memory, bandwidth, and computation beca...
Chao-Chung Cheng, Chia-Kai Liang, Homer H. Chen, L...
In this report, we consider whether statistical regularities in natural images might be exploited to provide an improved selection criterion for interest points. One approach that ...