Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
Lei Li, Wenjie Fu, Fan Guo, Todd C. Mowry, Christo...
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
MapReduce provides a parallel and scalable programming model for data-intensive business and scientific applications. MapReduce and its de facto open source project, called Hadoop...
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
The caching behavior of multimedia applications has been described as having high instruction reference locality within small loops, very large working sets, and poor data cache p...