This paper considers the problem of learning cellular signaling networks from incomplete measurements of pathway activity. Cells respond to environmental changes (e.g., starvation...
Possibilistic networks are important tools for dealing with uncertain pieces of information. For multiplyconnected networks, it is well known that the inference process is a hard ...
The ability to discover the AS-level path between two end-points is valuable for network diagnosis, performance optimization, and reliability enhancement. Virtually all existing t...
Automotive companies are forced to continuously extend and improve their product line-up. However, increasing diversity, higher design complexity, and shorter development cycles c...
Axel Blumenstock, Christoph Schlieder, Markus M&uu...
Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person’s...