Online subspace learning and imputation by tensor-ring decomposition

DOI10.1016/J.NEUNET.2022.05.023WikidataQ114145547 ScholiaQ114145547MaRDI QIDQ6488720

Jinshi Yu, Tao Zou, Guoxu Zhou

Publication date: 17 October 2023

Published in: Neural Networks (Search for Journal in Brave)

zbMATH Keywords

low rankstreaming datatensor ring decompositiononline tensor completion

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Unnamed Item
• Tensor Decompositions and Applications
• Canonical polyadic decomposition of third-order tensors: relaxed uniqueness conditions and algebraic algorithm
• Low-rank tensor completion by Riemannian optimization
• An efficient matrix bi-factorization alternative optimization method for low-rank matrix recovery and completion
• Tensor \(N\)-tubal rank and its convex relaxation for low-rank tensor recovery
• Multiple graphs learning with a new weighted tensor nuclear norm
• Low-rank tensor constrained co-regularized multi-view spectral clustering
• Hybrid tensor decomposition in neural network compression
• Manifold regularized matrix completion for multi-label learning with ADMM
• Tensor completion and low-n-rank tensor recovery via convex optimization
• New Uniqueness Conditions for the Canonical Polyadic Decomposition of Third-Order Tensors
• Fast Nonnegative Matrix/Tensor Factorization Based on Low-Rank Approximation
• Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors
• Efficient Tensor Completion for Color Image and Video Recovery: Low-Rank Tensor Train
• An Iterative Reweighted Method for Tucker Decomposition of Incomplete Tensors
• Smooth PARAFAC Decomposition for Tensor Completion
• Double Coupled Canonical Polyadic Decomposition for Joint Blind Source Separation

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