An inexact continuation accelerated proximal gradient algorithm for lown-rank tensor recovery

DOI10.1080/00207160.2013.854881zbMath1302.90151OpenAlexW1999750181MaRDI QIDQ2935378

Hui Hui Liu, Zhan-jie Song

Publication date: 29 December 2014

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160.2013.854881

zbMATH Keywords

singular value decompositionnuclear normtensor completionproximal gradientlow \textit{n}-rank tensor

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Control/observation systems with incomplete information (93C41)

Cites Work

• Tensor Decompositions and Applications
• Fixed point and Bregman iterative methods for matrix rank minimization
• A Singular Value Thresholding Algorithm for Matrix Completion
• Tensor completion and low-n-rank tensor recovery via convex optimization
• A numerical algorithm for image sequence inpainting that preserves fine textures
• Tensor rank is NP-complete
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Sparse Approximate Solutions to Linear Systems
• For most large underdetermined systems of linear equations the minimal 𝓁₁‐norm solution is also the sparsest solution
• Nonlinear Programming
• Compressed sensing
• Convergence of a block coordinate descent method for nondifferentiable minimization

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