We consider efficient methods for the recovery of block-sparse signals--i.e., sparse signals that have nonzero entries occurring in clusters--from an underdetermined system of line...
In this paper, we propose a novel approach to model shape variations. It encodes sparsity, exploits geometric redundancy, and accounts for the different degrees of local variation...
We propose a new scheme, named contourlet, that provides a flexible multiresolution, local and directional image expansion. The contourlet transform is realized efficiently via a ...
Categorizing multiple objects in images is essentially a structured prediction problem: the label of an object is in general dependent on the labels of other objects in the image....
Qinfeng Shi, Luping Zhou, Li Cheng, Dale Schuurman...
GSAT is a randomized greedy local repair procedure that was introduced for solving propositional satis ability and constraint satisfaction problems. We present an improvement to G...