Modeling Internet growth is important both for understanding the current network and to predict and improve its future. To date, Internet models have typically attempted to explai...
: Prediction of the quality attributes of software architectures requires technologies that enable the application of analytic theories to component models. However, available anal...
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...