The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
We show that relational algebra calculations for incomplete databases, probabilistic databases, bag semantics and whyprovenance are particular cases of the same general algorithms...
Motion analysis is an important component of surveillance, video annotation and many other applications. Current work focuses on the tracking of moving entities, the representatio...
Stergios Poularakis, Alexia Briassouli, Ioannis Ko...
Some physical aspects related to the limit operations of the Thomson lamp are discussed. Regardless of the formally unbounded and even infinite number of “steps” involved, the...