This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
The rapid need for high bandwidth and low latency communication in distributed real-time systems is driving system architects towards high-speed switches developed for high volume...
This paper contributes and evaluates a model and a methodology for implementing parallel wavefront algorithms on the Cell Broadband Engine. Wavefront algorithms are vital in sever...
Ashwin M. Aji, Wu-chun Feng, Filip Blagojevic, Dim...
Fisher score and Laplacian score are two popular feature selection algorithms, both of which belong to the general graph-based feature selection framework. In this framework, a fe...
Feiping Nie, Shiming Xiang, Yangqing Jia, Changshu...