We propose a strategy to decompose a polygon, containing zero or more holes, into “approximately convex” pieces. For many applications, the approximately convex components of ...
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
—Distributed Denial of Service attacks have recently emerged as one of the most potent, if not the greatest, weaknesses of the Internet. Previous solutions for this problem try t...
In this work we propose a hierarchical approach for labeling semantic objects and regions in scenes. Our approach is reminiscent of early vision literature in that we use a decompo...
The increasing size of integrated systems combined with deep submicron physical modeling details creates an explosion in RLC interconnect modeling complexity of unmanageable propo...
Michael W. Beattie, Satrajit Gupta, Lawrence T. Pi...