In statistical modelling, an investigator must often choose a suitable model among a collection of viable candidates. There is no consensus in the research community on how such a...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
In this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. The approa...
While guarded evaluation has proven an effective energy saving technique in arithmetic circuits, good methodologies do not exist for determining when and how to guard for maximal ...
This paper explores various aspects of the image decomposition problem using modern variational techniques. We aim at splitting an original image f into two components u and v, whe...