Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
A variety of remote sensing attacks allow adversaries to break flow confidentiality and gather mission-critical information in distributed systems. Such attacks are easily supple...
—To date many activity spotting approaches are static: once the system is trained and deployed it does not change anymore. There are substantial shortcomings of this approach, sp...
Given a classifier trained on relatively few training examples, active learning (AL) consists in ranking a set of unlabeled examples in terms of how informative they would be, if ...
Andrea Esuli, Diego Marcheggiani, Fabrizio Sebasti...
Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on...