Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
The focus of this work is on the estimation of quality of service (QoS) parameters seen by an application. Our proposal is based on end-to-end active measurements and statistical ...
A large number of variants of the Perceptron algorithm have been proposed and partially evaluated in recent work. One type of algorithm aims for noise tolerance by replacing the l...
Bayesian approaches to supervised learning use priors on the classifier parameters. However, few priors aim at achieving "sparse" classifiers, where irrelevant/redundant...
One-class support vector machines (1-SVMs) estimate the level set of the underlying density observed data. Aside the kernel selection issue, one difficulty concerns the choice of t...