Results 41 to 50 of about 9,784 (260)
Tensor Methods for Nonlinear Matrix Completion
SIAM Journal on Mathematics of Data Science, 2021 In the low-rank matrix completion (LRMC) problem, the low-rank assumption means that the columns (or rows) of the matrix to be completed are points on a low-dimensional linear algebraic variety. This paper extends this thinking to cases where the columns are points on a low-dimensional nonlinear algebraic variety, a problem we call Low Algebraic ...
Greg Ongie +4 more
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Riemannian preconditioning for tensor completion
CoRR, 2015 We propose a novel Riemannian preconditioning approach for the tensor completion problem with rank constraint. A Riemannian metric or inner product is proposed that exploits the least-squares structure of the cost function and takes into account the structured symmetry in Tucker decomposition.
Hiroyuki Kasai, Bamdev Mishra
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe task of hyperspectral image completion generally involves random missing entries completion, stripes inpainting, and cloud removal, which can enhance the accuracy of subsequent image analysis.
Yao Li, Yujie Zhang, Hongwei Li
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Provable Tensor-Train Format Tensor Completion by Riemannian Optimization
CoRR, 2021 The tensor train (TT) format enjoys appealing advantages in handling structural high-order tensors. The recent decade has witnessed the wide applications of TT-format tensors from diverse disciplines, among which tensor completion has drawn considerable attention.
Cai, Jianfeng, Li, Jingyang, Xia, Dong
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Accelerated Low-Rank Tensor Completion via Projected Tensor Block Coordinate Descent
IEEE AccessThe low-rank tensor completion problem aims to find a low-rank approximation of a tensor by filling in missing entries from partially observed entries to enhance the accuracy of the tensor data analysis.
Geunseop Lee
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A Novel Truncated Normal Tensor Completion Method for Multi-Source Fusion Data
MathematicsCompleting traffic data is a basic requirement for intelligent transportation systems. However, completing spatiotemporal traffic data poses a significant challenge, especially for high-dimensional data with complex missing mechanisms. Various completion
Yongmei Zhao
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Multi-Feature Tensor Neighborhood Preserving Embedding for 3D Facial Expression Recognition
IEEE Access, 2021 To investigate an effective representation model for 3D facial expression recognition, this paper proposes a multi-feature tensor neighborhood preserving embedding (MFTNPE) method, which seeks various attribute features from raw textured shape scan ...
Yajie Jiang, Qiuqi Ruan
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Nonlinear Transform Induced Tensor Nuclear Norm for Tensor Completion
Journal of Scientific Computing, 2022 Nonlinear transform, tensor nuclear norm, proximal alternating minimization, tensor ...
Ben-Zheng Li +4 more
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Rail transit OD‐matrix completion via manifold regularized tensor factorisation
IET Intelligent Transport Systems, 2021 Urban rail transit has become an indispensable mode in major cities worldwide regarding the advantages of large capacity, high speed, punctuality, and environmental protection.
Hanxuan Dong +5 more
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Completely positive biquadratic tensors
Applied Mathematics LettersIn this paper, we systemically introduce completely positive biquadratic (CPB) tensors and copositive biquadratic tensors. We show that all weakly CPB tensors are sum of squares tensors, the CPB tensor cone and the copositive biquadratic tensor cone are dual cone to each other.
Liqun Qi +3 more
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