Low Tensor-Ring Rank Completion by Parallel Matrix Factorization.

IEEE Transactions on Neural Networks and Learning Systems(2021)

引用 31|浏览85
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摘要
Tensor-ring (TR) decomposition has recently attracted considerable attention in solving the low-rank tensor completion (LRTC) problem. However, due to an unbalanced unfolding scheme used during the update of core tensors, the conventional TR-based completion methods usually require a large TR rank to achieve the optimal performance, which leads to high computational cost in practical applications....
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关键词
Tensile stress,Computational efficiency,Computational modeling,Matrix decomposition,Automation,Complexity theory,Learning systems
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