Probabilistic inference in graphical models is a prevalent task in statistics and artificial intelligence. The ability to perform this inference task efficiently is critical in l...
The paper presents a persuasive web application that stimulates residential energy conservation. The users of the application received consumption feedback that is based on electr...
Tobias Graml, Claire-Michelle Loock, Michael Baeri...
We present an original information theoretic measure of heart motion based on the Shannon's differential entropy (SDE), which allows heart wall motion abnormality detection. B...
Kumaradevan Punithakumar, Ismail Ben Ayed, Ian G. ...
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
In this paper we introduce a novel image descriptor enabling accurate object categorization even with linear models. Akin to the popular attribute descriptors, our feature vector ...