Self representation based methods for tensor completion problem
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Publication:6653547
DOI10.1016/j.cam.2024.116297MaRDI QIDQ6653547
Fatemeh Shakeri, Faezeh Aghamohammadi
Publication date: 16 December 2024
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Tensor Decompositions and Applications
- Parallel matrix factorization for low-rank tensor completion
- Tucker factorization with missing data with application to low-\(n\)-rank tensor completion
- Factorization strategies for third-order tensors
- Fixed point and Bregman iterative methods for matrix rank minimization
- An alternating direction algorithm for matrix completion with nonnegative factors
- Tensor-tensor products with invertible linear transforms
- Tensor completion using total variation and low-rank matrix factorization
- Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm
- Riemannian conjugate gradient descent method for fixed multi rank third-order tensor completion
- Matrix factorization for low-rank tensor completion using framelet prior
- Robust Schatten-\(p\) norm based approach for tensor completion
- A non-convex tensor rank approximation for tensor completion
- Dictionary Learning for Noisy and Incomplete Hyperspectral Images
- A Singular Value Thresholding Algorithm for Matrix Completion
- Tensor completion and low-n-rank tensor recovery via convex optimization
- Matrix completion via an alternating direction method
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- A Multilinear Singular Value Decomposition
- Total Variation Regularized Tensor RPCA for Background Subtraction From Compressive Measurements
- Robust low-rank tensor factorization by cyclic weighted median
- Sparse Nonnegative Tensor Factorization and Completion With Noisy Observations
- Truncated Low-Rank and Total p Variation Constrained Color Image Completion and its Moreau Approximation Algorithm
- Third-Order Tensors as Operators on Matrices: A Theoretical and Computational Framework with Applications in Imaging
- A Learnable Group-Tube Transform Induced Tensor Nuclear Norm and Its Application for Tensor Completion
- Trainable subspaces for low rank tensor completion: model and analysis
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