Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Descr...
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...
In wireless networks, secure multicast protocols are more difficult to implement efficiently due to the dynamic nature of the multicast group and the scarcity of bandwidth at the ...
We demonstrate NetTrails, a declarative platform for maintaining and interactively querying network provenance in a distributed system. Network provenance describes the history an...
Wenchao Zhou, Qiong Fei, Shengzhi Sun, Tao Tao, An...