Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
KDD is a complex and demanding task. While a large number of methods has been established for numerous problems, many challenges remain to be solved. New tasks emerge requiring th...
Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Mar...
Commitment-modeled protocols enable flexible and robust interactions among agents. However, existing work has focused on features and capabilities of protocols without considerin...
The emergence of power as a first-class design constraint has fueled the proposal of a growing number of run-time power optimizations. Many of these optimizations trade-off power...
With the increasing number of processors in modern HPC(High Performance Computing) systems, there are two emergent problems to solve. One is scalability, the other is fault tolera...