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Practical Compressive Sensing with Toeplitz and Circulant Matrices
Compressive sensing encodes a signal into a relatively small number of incoherent linear measurements. In theory, the optimal incoherence is achieved by completely random measurement matrices. However, such matrices are ...
Solving a Low-Rank Factorization Model for Matrix Completion by a Non-linear Successive Over-Relaxation Algorithm
The matrix completion problem is to recover a low-rank matrix from a subset of its entries. The main solution strategy for this problem has been based on nuclear-norm minimization which requires computing singular value ...
An Alternating Direction Algorithm for Nonnegative Matrix Factorization
We extend the classic alternating direction method for convex optimization to solving the non-convex, non- negative matrix factorization problem and conduct several carefully designed numerical experiments to compare the ...
Convergence of a Class of Stationary Iterative Methods for Saddle Point Problems
A unified convergence result is derived for an entire class of stationary iterative methods for solving equality constrained quadratic programs or saddle point problems. This class is constructed from essentially all ...