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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 ...
A Feasible Method for Optimization with Orthogonality Constraints
Minimization with orthogonality constraints (e.g., X'X = I) and/or spherical constraints (e.g., ||x||_2 = 1) has wide applications in polynomial optimization, combinatorial optimization, eigenvalue problems, sparse PCA, ...
Trust, But Verify: Fast and Accurate Signal Recovery from 1-bit Compressive Measurements
The recently emerged compressive sensing (CS) framework aims to acquire signals at reduced sample rates compared to the classical Shannon-Nyquist rate. To date, the CS theory has assumed primarily real-valued measurements; ...