Robust Tensor Completion: Equivalent Surrogates, Error Bounds, and Algorithms
DOI10.1137/21M1429539zbMath1497.65080OpenAlexW4281401255WikidataQ114074014 ScholiaQ114074014MaRDI QIDQ5863527
Xueying Zhao, Defeng Sun, Libin Zheng, Min-Ru Bai
Publication date: 1 June 2022
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/21m1429539
error boundsimpulse noiseproximal majorization-minimizationDC equivalent surrogatesrobust low-rank tensor completion
Nonconvex programming, global optimization (90C26) Computing methodologies for image processing (68U10) Multilinear algebra, tensor calculus (15A69) Numerical methods for low-rank matrix approximation; matrix compression (65F55)
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- Nearly unbiased variable selection under minimax concave penalty
- Fast Algorithms for Large-Scale Generalized Distance Weighted Discrimination
- A rank-corrected procedure for matrix completion with fixed basis coefficients
- Proximal alternating linearized minimization for nonconvex and nonsmooth problems
- Statistics for high-dimensional data. Methods, theory and applications.
- Factorization strategies for third-order tensors
- Robust matrix completion
- Alternating direction method of multipliers with difference of convex functions
- Characterization of the subdifferential of some matrix norms
- Low Tucker rank tensor recovery via ADMM based on exact and inexact iteratively reweighted algorithms
- Global convergence of ADMM in nonconvex nonsmooth optimization
- Equivalent Lipschitz surrogates for zero-norm and rank optimization problems
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- Nonconvex optimization for robust tensor completion from grossly sparse observations
- Noisy low-rank matrix completion with general sampling distribution
- Strong oracle optimality of folded concave penalized estimation
- Analysis of individual differences in multidimensional scaling via an \(n\)-way generalization of ``Eckart-Young decomposition
- Robust principal component analysis?
- Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality
- An Adaptive Correction Approach for Tensor Completion
- Variational Analysis
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Tensor-Based Formulation and Nuclear Norm Regularization for Multienergy Computed Tomography
- A TVSCAD approach for image deblurring with impulsive noise
- Exact Tensor Completion Using t-SVD
- Tensor Decomposition for Signal Processing and Machine Learning
- Sparse Approximate Solutions to Linear Systems
- Convergence of alternating direction method for minimizing sum of two nonconvex functions with linear constraints
- Alternating Direction Method of Multipliers for a Class of Nonconvex and Nonsmooth Problems with Applications to Background/Foreground Extraction
- Third-Order Tensors as Operators on Matrices: A Theoretical and Computational Framework with Applications in Imaging
- Difference-of-Convex Learning: Directional Stationarity, Optimality, and Sparsity
- Most Tensor Problems Are NP-Hard
- Convex Analysis
- A Schur complement based semi-proximal ADMM for convex quadratic conic programming and extensions
- A Corrected Tensor Nuclear Norm Minimization Method for Noisy Low-Rank Tensor Completion
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