Abstract—We propose a robust fitting framework, called Adaptive Kernel-Scale Weighted Hypotheses (AKSWH), to segment multiplestructure data even in the presence of a large number...
A method is presented for modeling application performance on parallel computers in terms of the performance of microkernels from the HPC Challenge benchmarks. Specifically, the a...
Tuning parallel code can be a time-consuming and difficult task. We present our approach to automate the performance analysis of OpenMP applications that is based on the notion of ...
Outlier analysis is an important task in data mining and has attracted much attention in both research and applications. Previous work on outlier detection involves different type...
Wen Jin, Yuelong Jiang, Weining Qian, Anthony K. H...
This paper describes our experience with applying data mining techniques to the problem of fraud detection in spatio-temporal health data in Medicare Australia. A modular framework...
Kee Siong Ng, Yin Shan, D. Wayne Murray, Alison Su...