Low-Rank Positive Semidefinite Matrix Recovery From Corrupted Rank-One Measurements
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DOI: 10.1109/tsp.2016.2620109
Abstract: We study the problem of estimating a low-rank positive semidefinite (PSD) matrix from a set of rank-one measurements using sensing vectors composed of i.i.d. standard Gaussian entries, which are possibly corrupted by arbitrary outliers. This… read more here.
Keywords: rank positive; matrix; low rank; positive semidefinite ... See more keywords