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A Deterministic Theory of Low Rank Matrix Completion.

Authors :
Chatterjee, Sourav
Source :
IEEE Transactions on Information Theory. Dec2020, Vol. 66 Issue 12, p8046-8055. 10p.
Publication Year :
2020

Abstract

The problem of completing a large low rank matrix using a subset of revealed entries has received much attention in the last ten years. The main result of this paper gives a necessary and sufficient condition, stated in the language of graph limit theory, for a sequence of matrix completion problems with arbitrary missing patterns to be asymptotically solvable. It is then shown that a small modification of the Candès–Recht nuclear norm minimization algorithm provides the required asymptotic solution whenever the sequence of problems is asymptotically solvable. The theory is fully deterministic, with no assumption of randomness. A number of open questions are listed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189448
Volume :
66
Issue :
12
Database :
Academic Search Index
Journal :
IEEE Transactions on Information Theory
Publication Type :
Academic Journal
Accession number :
147291940
Full Text :
https://doi.org/10.1109/TIT.2020.3019569