GlobalLinearandLocalSuperlinearConvergenceof IRLSforNon-SmoothRobustRegression

Neural Information Processing Systems 

Theresults showthat(1)IRLS canhandle alargernumber ofoutliers thanother methods, (2) it is faster than competing methods at the same level of accuracy, (3) it restores a sparsely corrupted face image with satisfactory visual quality.

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