This paper shows that in education and training systems LOM can be used to map the structure of courses. The necessary extension of the aggregation level is introduced. The descrip...
Stefan Hoermann, Cornelia Seeberg, Luka Divac-Krni...
Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function be...
Renato L. G. Cavalcante, Alex Rogers, Nicholas R. ...
Recursive graphical models usually underlie the statistical modelling concerning probabilistic expert systems based on Bayesian networks. This paper de nes a version of these mode...
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
We present a time-efficient approach to index objects moving on the plane to efficiently answer range queries about their future positions. Each object is moving with non small ve...
Spyros Sioutas, George Papaloukopoulos, Kostas Tsi...