AI RESEARCH
Low Rank Tensor Completion via Adaptive ADMM
arXiv CS.LG
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ArXi:2605.03736v1 Announce Type: cross We consider a novel algorithm, for the completion of partially observed low-rank tensors, as a generalization of matrix completion. The proposed low-rank tensor completion (TC) method builds on the conventional nuclear norm (NN) minimization-based low-rank TC paradigm, by leveraging the alternating direction method of multipliers (ADMM) optimization framework.