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Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications

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Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications - Oreifej, Omar, and Shah, Mubarak
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Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of ...

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Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications 2016, Springer, Cham

ISBN-13: 9783319352480

Trade paperback

Robust Subspace Estimation Using Low-Rank Optimization: Theory and Applications 2014, Springer International Publishing AG, Cham

ISBN-13: 9783319041834

Hardcover