Tensor completion via bilevel minimization with fixed-point constraint to estimate missing elements in noisy data

DOI10.1007/s10444-020-09841-8zbMath1468.90096OpenAlexW3126581574MaRDI QIDQ2026112

Souad Mohaoui, Abdelilah Hakim, Said Raghay

Publication date: 18 May 2021

Published in: Advances in Computational Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10444-020-09841-8

zbMATH Keywords

fixed-pointsparsity priorbilevel minimizationtensor completion and denoisingtruncated nuclear norm

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Related Items (1)

A non-convex denoising model for impulse and Gaussian noise mixture removing using bi-level parameter identification

Cites Work

• Parallel matrix factorization for low-rank tensor completion
• Bilevel optimization for calibrating point spread functions in blind deconvolution
• Fixed point and Bregman iterative methods for matrix rank minimization
• Necessary optimality conditions for bilevel set optimization problems
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• Exact matrix completion via convex optimization
• Mathematical Methods in Image Reconstruction
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• Bilevel Optimization with Nonsmooth Lower Level Problems
• Convergence Rates in Forward--Backward Splitting
• Necessary Optimality Conditions for Optimization Problems with Variational Inequality Constraints
• A Truncated Nuclear Norm Regularization Method Based on Weighted Residual Error for Matrix Completion
• Constraint Qualifications and KKT Conditions for Bilevel Programming Problems

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