Adaptive tensor networks decomposition for high-order tensor recovery and compression

DOI10.1016/J.INS.2023.01.086OpenAlexW4320004468MaRDI QIDQ6127129

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Publication date: 10 April 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2023.01.086

zbMATH Keywords

tensor decompositiontensor networksrobust tensor principal component analysis

Mathematics Subject Classification ID

Computer science (68-XX) Operations research, mathematical programming (90-XX)

Cites Work

• Tensor Decompositions and Applications
• Tensor-Train Decomposition
• A practical introduction to tensor networks: Matrix product states and projected entangled pair states
• Tensor \(N\)-tubal rank and its convex relaxation for low-rank tensor recovery
• Exact matrix completion via convex optimization
• Tree Adaptive Approximation in the Hierarchical Tensor Format
• A Singular Value Thresholding Algorithm for Matrix Completion
• Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
• Tensor Network Contractions
• Weighted Tensor Rank-1 Decomposition for Nonlocal Image Denoising
• Infrared Patch-Image Model for Small Target Detection in a Single Image
• Most Tensor Problems Are NP-Hard
• Auto-weighted robust low-rank tensor completion via tensor-train

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