This paper presents an extensive empirical evaluation of an interprocedural parallelizing compiler, developed as part of the Stanford SUIF compiler system. The system incorporates...
Mary W. Hall, Saman P. Amarasinghe, Brian R. Murph...
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze e...
We present an experimental framework for Entity Mention Detection in which two different classifiers are combined to exploit Data Redundancy attained through the annotation of a l...
Most object recognition systems require large databases of real images for classifier training. To collect real images for this purpose is a difficult and expensive process. This ...
Computer problem diagnosis remains a serious challenge to users and support professionals. Traditional troubleshooting methods relying heavily on human intervention make the proce...
Chun Yuan, Ni Lao, Ji-Rong Wen, Jiwei Li, Zheng Zh...