This paper addresses the question of producing modular sequential imperative code from synchronous data-flow networks. Precisely, given a system with several input and output flow...
In this note, we address the theoretical properties of p, a class of compressed sensing decoders that rely on p minimization with p (0, 1) to recover estimates of sparse and compr...
We propose a fast algorithm for solving the ℓ1-regularized minimization problem minx∈Rn µ x 1 + Ax − b 2 2 for recovering sparse solutions to an undetermined system of linea...
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...