Local reconstruction of low‐rank matrices and subspaces

We study the problem of reconstructing a low‐rank matrix, where the input is an n × m matrix M over a field F and the goal is to reconstruct a (near‐optimal) matrix M′ that is low‐rank and close to M under some distance function Δ. Furthermore, the reconstruction must be local, i.e., provides access...

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Bibliographic Details

Published in:	Random structures & algorithms Vol. 51; no. 4; pp. 607 - 630
Main Authors:	David, Roee, Goldenberg, Elazar, Krauthgamer, Robert
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc 01.12.2017
Subjects:	Algorithms Columns (structural) Data storage Data structures local reconstruction low‐rank matrix reconstruction Machine learning matrix rigidity Preprocessing Reconstruction Statistical analysis sublinear‐time algorithms subspace approximation Subspaces
ISSN:	1042-9832, 1098-2418
Online Access:	Get full text
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