Designing a computer-supported learning scenario involving a constructivist approach of learning lays on a paradox. On the one hand, learning flows must be precisely described –...
Anne Lejeune, Muriel Ney, Armin Weinberger, Margus...
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
In supervised learning, we commonly assume that training and test data are sampled from the same distribution. However, this assumption can be violated in practice and then standa...
We present SETS, an architecture for efficient search in peer-to-peer networks, building upon ideas drawn from machine learning and social network theory. The key idea is to arran...
Abstract. Level set methods are a popular way to solve the image segmentation problem in computer image analysis. A contour is implicitly represented by the zero level of a signed ...