Tensor Completion for Estimating Missing Values in Visual Data
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- Type
- article
- Published
- 2009-09-01
- Cited by
- 2,103
- References
- 59
- OpenAlex
- https://openalex.org/W2091449379
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:82504
Keywords
Matrix completion, Tensor (intrinsic definition), Algorithm, Missing data, Matrix norm
References
- EFFICIENT METHODS IN CONVEX PROGRAMMING
- Quantum state tomography via compressed sensing.
- Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization
- Matrix methods in data mining and pattern recognition
- Estimation of low-rank tensors via convex optimization
- A collaborative framework for 3D alignment and classification of heterogeneous subvolumes in cryo-electron tomography
- Some mathematical notes on three-mode factor analysis
- SDPT3 -- A Matlab Software Package for Semidefinite Programming
- A rank minimization heuristic with application to minimum order system approximation
- An accelerated gradient method for trace norm minimization
- Matrix completion from a few entries
- Fast Singular Value Thresholding without Singular Value Decomposition
- Fixed point and Bregman iterative methods for matrix rank minimization
- Visual saliency detection via rank-sparsity decomposition
- Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
- Stable Principal Component Pursuit
- Spatiotemporal Inpainting for Recovering Texture Maps of Occluded Building Facades
- Hole-Filling by Rank Sparsity Tensor Decomposition for Medical Imaging
- Tensor completion and low-n-rank tensor recovery via convex optimization
- Most Tensor Problems Are NP-Hard
Cited by
- Adaptive Multinomial Matrix Completion
- Low-Rank Total Variation for Image Super-Resolution
- Bayesian Robust Tensor Factorization for Incomplete Multiway Data
- Matrix Analysis and Applications
- Hybrid Singular Value Thresholding for Tensor Completion
- Low-Rank Matrix Recovery via Efficient Schatten p-Norm Minimization
- Provable sparse tensor decomposition
- A Comparative Analysis of Tensor Decomposition Models Using Hyper Spectral Image
- Convergence rate of Bayesian tensor estimator and its minimax optimality
- Compressive Higher-order Sparse and Low-Rank Acquisition with a Hyperspectral Light Stage
- Riemannian preconditioning for tensor completion
- Robust orthogonal matrix factorization for efficient subspace learning
- Low-rank and sparse reconstruction in dynamic magnetic resonance imaging via proximal splitting methods
- Efficient end-to-end monitoring for fault management in distributed systems. (La surveillance efficace de bout-à-bout pour la gestion des pannes dans les systèmes distribués)
- On the Design and Analysis of Operator-Splitting Schemes
- Group-based image decomposition using 3-D cartoon and texture priors
- Nonlocal image denoising via adaptive tensor nuclear norm minimization
- Tensor completion using total variation and low-rank matrix factorization
- Group Orbit Optimization: A Unified Approach to Data Normalization
- Trace Norm Regularized Tensor Classification and Its Online Learning Approaches
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