Automated generators for synthetic models and data can play a crucial role in designing new algorithms/modelframeworks, given the sparsity of benchmark models for empirical analys...
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
Abstract. There is currently a large interest in relational probabilistic models. While the concept of context-specific independence (CSI) has been well-studied for models such as ...
Due to the better utilization of computational and communication resources and the improved coordination of application subsystems, designers of large distributed embedded systems...
Network infrastructures are nowadays getting more and more complex as security considerations and technical needs like network address translation are blocking traffic and protocol...