Robust and Scalable Column/Row Sampling from Corrupted Big Data

18 Nov 2016 Mostafa Rahmani George Atia

Conventional sampling techniques fall short of drawing descriptive sketches of the data when the data is grossly corrupted as such corruptions break the low rank structure required for them to perform satisfactorily. In this paper, we present new sampling algorithms which can locate the informative columns in presence of severe data corruptions... (read more)

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