A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
: Although the Java bytecode has numerous advantages, it also has certain shortcomings such as its slow execution speed and difficulty of analysis. In order to overcome such disadv...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
ion of discrete abstractions of arbitrary memory span for nonlinear sampled systems Gunther Reißig⋆ Technische Universit¨at Berlin, Fakult¨at Elektrotechnik und Informatik, He...