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Dense error correction for low-rank matrices via Principal Component Pursuit.

, , , , and . ISIT, page 1513-1517. IEEE, (2010)

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Compressive principal component pursuit., , , and . ISIT, page 1276-1280. IEEE, (2012)Dense error correction for low-rank matrices via Principal Component Pursuit., , , , and . ISIT, page 1513-1517. IEEE, (2010)Face recognition by sparse representation., , , , , and . Compressed Sensing, Cambridge University Press, (2012)Fast l1-minimization algorithms and an application in robust face recognition: A review., , , and . ICIP, page 1849-1852. IEEE, (2010)Principal Component Pursuit with reduced linear measurements., , , and . ISIT, page 1281-1285. IEEE, (2012)Nearest-Subspace Patch Matching for face recognition under varying pose and illumination., , , , and . FG, page 1-8. IEEE Computer Society, (2008)Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery., , , , , and . ACCV (3), volume 6494 of Lecture Notes in Computer Science, page 703-717. Springer, (2010)Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices, , , and . CoRR, (2009)Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization., , , , and . NIPS, page 2080-2088. Curran Associates, Inc., (2009)Separation of a subspace-sparse signal: Algorithms and conditions., , and . ICASSP, page 3141-3144. IEEE, (2009)