In this paper, we consider the problem of nding llpreserving ordering of a sparse symmetric and positive de nite matrix such that the reordered matrix is suitable for parallel fac...
The 2- 1 compressed sensing minimization problem can be solved efficiently by gradient projection. In imaging applications, the signal of interest corresponds to nonnegative pixel...
Zachary T. Harmany, Daniel Thompson, Rebecca Wille...
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
We propose a novel framework to reconstruct the left ventricle (LV)’s 3D surface from sparse tagged-MRI (tMRI). First we acquire an initial surface mesh from a dense tMRI. Then ...
We consider the problem of estimating and detecting sparse signals over a large area of an image or other medium. We introduce a novel cost function that captures the tradeoff bet...