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Malware data are typically depicted with extremely high-dimensional features, which lays an excessive computational burden on detection methods. For the sake of effectiveness and efficiency, feature selection is an indispensable part for malware detection. In this paper, we propose an ensemble feature selection method with integration of discriminative and representative properties for malware detection...
In social network, correlation estimation is a critical problem with promising application prospect. Numerical records of the interaction can serve as informative reflections of the correlation between users. However, due to the noise during data acquisition and storage as well as the privacy concern, the interaction data are usually partially observed. Moreover, even if the complete interaction is...
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