Differentiating anomalous network activity from normal network traffic is difficult and tedious. A human analyst must search through vast amounts of data to find anomalous sequenc...
We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online meth...
This paper presents a method that assists in maintaining a rule-based named-entity recognition and classification system. The underlying idea is to use a separate system, construc...
Georgios Petasis, Frantz Vichot, Francis Wolinski,...
During a project examining the use of machine learning techniques for oil spill detection, we have encountered several essential questions that we believe deserve the attention of ...
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...