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dc.contributor.authorCarlos, Beltrán-
dc.contributor.authorPaul, Breiding-
dc.contributor.authorNick, Vannieuwenhoven-
dc.date.accessioned2023-04-03T08:10:18Z-
dc.date.available2023-04-03T08:10:18Z-
dc.date.issued2022-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/7446-
dc.descriptionCC BYvi
dc.description.abstractThe tensor rank decomposition, or canonical polyadic decomposition, is the decomposition of a tensor into a sum of rank-1 tensors. The condition number of the tensor rank decomposition measures the sensitivity of the rank-1 summands with respect to structured perturbations. Those are perturbations preserving the rank of the tensor that is decomposed. On the other hand, the angular condition number measures the perturbations of the rank-1 summands up to scaling. We show for random rank-2 tensors that the expected value of the condition number is infinite for a wide range of choices of the density.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectsum of rank-1 tensorsvi
dc.subjectstructured perturbationsvi
dc.titleThe Average Condition Number of Most Tensor Rank Decomposition Problems is Infinitevi
dc.typeBookvi
Appears in CollectionsOER - Khoa học Tự nhiên

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