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Showing 1 to 1 of 1 for “"machine learning; computer vision; subspace clustering; low rank; compressive sensing;"”.
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Robust learning with low-dimensional structure: theory,algorithms and applications
In this thesis, we study the robust learning of low-dimensional structures when there are uncertainties in the data. In particular, we consider two structures that are common in real problems: ?low-rank subspace model? that underlies matrix completion and Robust PCA, and ?union-of-subspace model? …