An appearance-based approach to track an object that may undergo appearance change is proposed. Unlike recent methods that store a detailed representation of object's appeara...
There are two main classes of decoding algorithms for "compressed sensing," those which run time time polynomial in the signal length and those which use sublinear resou...
The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the ...
Sparse representation has found applications in numerous domains and recent developments have been focused on the convex relaxation of the 0-norm minimization for sparse coding (i...
Abstract. A number of techniques are described for solving sparse linear systems on parallel platforms. The general approach used is a domaindecomposition type method in which a pr...