We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalizatio...
The problem of maintaining geometric structures for points in motion has been well studied over the years. Much theoretical work to date has been based on the assumption that point...
With continuing increase in soft error rates, its foreseeable that multiple faults will eventually need to be considered when modeling circuit sensitivity and evaluating faulttole...
Christian J. Hescott, Drew C. Ness, David J. Lilja
—Adapting transmission parameters to the future channel state is an appealing approach to improve efficiency in wireless communication. Adaptation requires predicting the chann...
Ana Aguiar, Holger Karl, Adam Wolisz, Horst Miesme...
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...