We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
The dimensionality of face space is measured objectively in a psychophysical study. Within this framework we obtain a measurement of the dimension for the human visual system. Usi...
—In embedded computing we face a continuously growing algorithm complexity combined with a constantly rising number of applications running on a single system. Multi-core systems...
Bastian Ristau, Torsten Limberg, Oliver Arnold, Ge...