We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
: One of the most important use-cases of Trusted Computing is Remote Attestation. It allows platforms to get a trustworthy proof of the loaded software and current configuration of...
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
As an important technique for data analysis, clustering has been employed in many applications such as image segmentation, document clustering and vector quantization. Divisive cl...
Enriching knowledge bases with multimedia information makes it possible to complement textual descriptions with visual and audio information. Such complementary information can he...