In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
We consider the problem of extracting informative exemplars from a data stream. Examples of this problem include exemplarbased clustering and nonparametric inference such as Gauss...
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
Finding structure in multiple streams of data is an important problem. Consider the streams of data owing from a robot's sensors, the monitors in an intensive care unit, or p...