Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
The ability to provide uniform shared-memory access to a significant number of processors in a single SMP node brings us much closer to the ideal PRAM parallel computer. In this pa...
David A. Bader, Ajith K. Illendula, Bernard M. E. ...
Abstract--This paper tackles a fundamental problem of network planning and dimensioning under EPON-WiMAX integration for next-generation wireless metropolitan-area broadband access...
Bin Lin, Pin-Han Ho, Xuemin Shen, Frank Chih-Wei S...
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...
In this paper, a programming model is presented which enables scalable parallel performance on multi-core shared memory architectures. The model has been developed for application...