Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
Through the algorthmic design patterns of data parallelism and task parallelism, the graphics processing unit (GPU) offers the potential to vastly accelerate discovery and innovat...
Jeremy S. Archuleta, Yong Cao, Thomas Scogland, Wu...
While many computer tutoring systems have long been delivered as desktop applications, these systems have only recently begun to appear on mobile devices. In this work we apply pri...
Quincy Brown, Dario D. Salvucci, Frank J. Lee, Vin...
Abstract. Recent sensor technologies have enabled the capture of users’ behavior data. Given the large amount of data currently available from sensor-equipped environments, it is...