This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
—More and more current software systems rely on non trivial coordination logic for combining autonomous services typically running on different platforms and often owned by diffe...
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...
Document representations can rapidly become unwieldy if they try to encapsulate all possible document properties, ranging tract structure to detailed rendering and layout. We pres...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...