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SIAMIS
2011
13 years 2 months ago
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Stephen Becker, Jérôme Bobin, Emmanue...
SIAMJO
2010
246views more  SIAMJO 2010»
13 years 5 months ago
A Singular Value Thresholding Algorithm for Matrix Completion
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...
Jian-Feng Cai, Emmanuel J. Candès, Zuowei S...
ISBI
2009
IEEE
14 years 2 months ago
Improving M/EEG Source Localization with an Inter-Condition Sparse Prior
The inverse problem with distributed dipoles models in M/EEG is strongly ill-posed requiring to set priors on the solution. Most common priors are based on a convenient ℓ2 norm....
Alexandre Gramfort, Matthieu Kowalski
CISS
2008
IEEE
14 years 1 months ago
Distributed processing in frames for sparse approximation
—Beyond signal processing applications, frames are also powerful tools for modeling the sensing and information processing of many biological and man-made systems that exhibit in...
Christopher J. Rozell
PC
2002
118views Management» more  PC 2002»
13 years 7 months ago
Parallel algorithms for indefinite linear systems
Saddle-point problems give rise to indefinite linear systems that are challenging to solve via iterative methods. This paper surveys two recent techniques for solving such problem...
Ahmed H. Sameh, Vivek Sarin