Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
Concept drifting in data streams often occurs unpredictably at any time. Currently many classification mining algorithms deal with this problem by using an incremental learning ap...
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
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...
This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and ...
Andrei Popescu-Belis, Alexander Clark, Maria Georg...