Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Finite element methods commonly use unstructured grids as the computational domain. As a matter of fact, the volume visualization of these unstructured grids is a time consuming t...
In this paper, a programming model is presented which enables scalable parallel performance on multi-core shared memory architectures. The model has been developed for application...
Bounded Model Checking (BMC) techniques have been used for formal hardware verification, with the help of tools such as GRASP (Generic search Algorithm for Satisfiability Proble...
We present a new interface for large-scale online conversations. Our technique, the Conversation Thumbnail, differs from existing discussion interfaces in two respects. First, it ...