Fast alternating linearization methods for minimizing the sum of two convex functions

Convergence of Fixed-Point Continuation Algorithms for Matrix Rank Minimization

(2011) Donald Goldfarb et al.   FOUNDATIONS OF COMPUTATIONAL MATHEMATICS

Robust principal component analysis?

(2011) Emmanuel J. Candès et al.   JOURNAL OF THE ACM

Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing

(2011) Junfeng Yang et al.   SIAM JOURNAL ON SCIENTIFIC COMPUTING

Fast Image Recovery Using Variable Splitting and Constrained Optimization

(2010) Manya V Afonso et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems

(2010) M V Afonso et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Matrix Completion From a Few Entries

(2010) Raghunandan H. Keshavan et al.   IEEE TRANSACTIONS ON INFORMATION THEORY

The Power of Convex Relaxation: Near-Optimal Matrix Completion

(2010) Emmanuel J. Candes et al.   IEEE TRANSACTIONS ON INFORMATION THEORY

Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization

(2010) Benjamin Recht et al.   SIAM REVIEW

Exact Matrix Completion via Convex Optimization

(2009) Emmanuel J. Candès et al.   FOUNDATIONS OF COMPUTATIONAL MATHEMATICS

Fixed point and Bregman iterative methods for matrix rank minimization

(2009) Shiqian Ma et al.   MATHEMATICAL PROGRAMMING

The Split Bregman Method for L1-Regularized Problems

(2009) Tom Goldstein et al.   SIAM Journal on Imaging Sciences

A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

(2009) Amir Beck et al.   SIAM Journal on Imaging Sciences

Regularization Methods for Semidefinite Programming

(2009) Jérôme Malick et al.   SIAM JOURNAL ON OPTIMIZATION

Fixed-Point Continuation for $\ell_1$-Minimization: Methodology and Convergence

(2008) Elaine T. Hale et al.   SIAM JOURNAL ON OPTIMIZATION