Data Communication and Computer Networking is a traditional undergraduate CS course. Classic teaching focuses on communication protocol and algorithm analysis, plus socket programm...
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Abstract. The heterogeneous and unreliable nature of distributed systems has created a distinct need for the inclusion of provenance within their design to allow for error correcti...
This paper describes Isis, a system that uses progressive multiples of timelines and event plots to support the iterative investigation of intrusions by experienced analysts using ...
Doantam Phan, J. Gerth, M. Lee, Andreas Paepcke, T...
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...