RIP-based performance guarantee for low-tubal-rank tensor recovery

DOI10.1016/j.cam.2020.112767OpenAlexW3003813531MaRDI QIDQ2306402

Feng Zhang, Wendong Wang, Yao Wang, Jian-Wen Huang, Jian-Jun Wang

Publication date: 23 March 2020

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1906.01774

zbMATH Keywords

tensor singular value decompositionregularizedlow-rank tensor recoverytensor restricted isometry property

Mathematics Subject Classification ID

Convex programming (90C25) Differential geometric aspects in vector and tensor analysis (53A45) Multilinear algebra, tensor calculus (15A69) Numerical solution to inverse problems in abstract spaces (65J22)

Related Items

Robust Recovery of Low-Rank Matrices and Low-Tubal-Rank Tensors from Noisy Sketches, Nonlocal robust tensor recovery with nonconvex regularization ^*

Uses Software

• tproduct

Cites Work

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