Modern unsteady (multi-)field visualizations require an effective reduction of the data to be displayed. From a huge amount of information the most informative parts have to be ext...
Heike Jänicke, Alexander Wiebel, Gerik Scheuerm...
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
In this paper we propose to use components for managing the increasing complexity in modern vehicular systems. Compared to other approaches, the distinguishing feature of our work...
In this paper, we present several general policies for deciding when to share probabilistic beliefs between agents for distributed monitoring. In order to evaluate these policies,...