Accurately predicting program behaviors (e.g., locality, dependency, method calling frequency) is fundamental for program optimizations and runtime adaptations. Despite decades of...
Kai Tian, Yunlian Jiang, Eddy Z. Zhang, Xipeng She...
A vital task facing government agencies and commercial organizations that report data is to represent the data in a meaningful way and simultaneously to protect the confidentialit...
Fred Glover, Lawrence H. Cox, Rahul Patil, James P...
In this paper, we propose a novel patch-based face hallucination framework, which employs a dual model to hallucinate different components associated with one facial image. Our mod...
Most approaches to model-based diagnosis describe a diagnosis for a system as a set of failing components that explains the symptoms. In order to characterize the typically very l...
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...