Smoothed Low Rank and Sparse Matrix Recovery by Iteratively Reweighted Least Squares Minimization

29 Jan 2014Canyi LuZhouchen LinShuicheng Yan

This work presents a general framework for solving the low rank and/or sparse matrix minimization problems, which may involve multiple non-smooth terms. The Iteratively Reweighted Least Squares (IRLS) method is a fast solver, which smooths the objective function and minimizes it by alternately updating the variables and their weights... (read more)

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