Motivated by applications in grid computing and projects management, we study multiprocessor scheduling in scenarios where there is uncertainty in the successful execution of jobs...
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
Whenever approximate 3D geometry is projectively texture-mapped from different directions simultaneously, annoyingly visible aliasing artifacts are the result. To prevent such gho...
Abstract-- This paper describes a symbolic algorithm for overapproximating reachability in Boolean programs with unbounded thread creation. The fix-point is detected by projecting ...
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...