Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
Nearly ten years after its first presentation and five years after its first application to operating systems, the suitability of AspectOriented Programming (AOP) for the devel...
Daniel Lohmann, Fabian Scheler, Reinhard Tartler, ...
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solu...
Lack of realistic benchmarks hinders efficient design and evaluation of analysis techniques for feature models. We extract a variability model from the code base of the Linux kerne...
Steven She, Rafael Lotufo, Thorsten Berger, Andrze...