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 ...
In this paper, we present a compiler strategy to optimize data accesses in regular array-intensive applications running on embedded multiprocessor environments. Specifically, we p...
Mahmut T. Kandemir, J. Ramanujam, Alok N. Choudhar...
We propose a distributed data management scheme for large data visualization that emphasizes efficient data sharing and access. To minimize data access time and support users wit...
Jinzhu Gao, Jian Huang, C. Ryan Johnson, Scott Atc...
Energy is increasingly a first-order concern in computer systems. Exploiting energy-accuracy trade-offs is an attractive choice in applications that can tolerate inaccuracies. Re...
Adrian Sampson, Werner Dietl, Emily Fortuna, Danus...
Wireless data broadcast has received a lot of attention from industries and academia in recent years. Access efficiency and energy conservation are two critical performance concer...