Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Probabilistic latent topic models have recently enjoyed much success in extracting and analyzing latent topics in text in an unsupervised way. One common deficiency of existing to...
We present an approach for applying symmetry reduction techniques to probabilistic model checking, a formal verification method for the quantitative analysis of systems with stocha...
—In many wireless ad-hoc networks it is important to find a route that delivers a message to the destination within a certain deadline (delay constraint). We propose to identify...
Matthew Brand, Petar Maymounkov, Andreas F. Molisc...
—Distributed denial-of-service attacks (DDoS) pose an immense threat to the Internet. The most studied solution is to let routers probabilistically mark packets with partial path...