Extracting information from data, often also called data analysis, is an important scienti c task. Statistical approaches, which use methods from probability theory and numerical a...
Bernd Fischer 0002, Johann Schumann, Thomas Pressb...
In this paper we propose the Merge framework, a general purpose programming model for heterogeneous multi-core systems. The Merge framework replaces current ad hoc approaches to p...
Michael D. Linderman, Jamison D. Collins, Hong Wan...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Instruction set customization accelerates the performance of applications by compressing the length of critical dependence paths and reducing the demands on processor resources. W...
Sami Yehia, Nathan Clark, Scott A. Mahlke, Kriszti...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...