Matrix completion and tensor rank

DOI10.1080/03081087.2015.1083565zbMath1346.15026arXiv1302.2639OpenAlexW1870903031MaRDI QIDQ2805654

H. G. J. Derksen

Publication date: 12 May 2016

Published in: Linear and Multilinear Algebra (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1302.2639

zbMATH Keywords

partial matrixtensor ranklow rank matrix completion problem

Mathematics Subject Classification ID

Multilinear algebra, tensor calculus (15A69) Matrix completion problems (15A83)

Related Items (1)

On the equivalence between low-rank matrix completion and tensor rank

Cites Work

• Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
• Orthogonal representations over finite fields and the chromatic number of graphs
• Exact matrix completion via convex optimization
• Tensor completion and low-n-rank tensor recovery via convex optimization
• Tensor rank is NP-complete
• Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
• Matrix Completion From a Few Entries
• The Power of Convex Relaxation: Near-Optimal Matrix Completion
• Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem
• Most Tensor Problems Are NP-Hard

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