Scaled Nuclear Norm Minimization for Low-Rank Tensor Completion

25 Jul 2017 Morteza Ashraphijuo Xiaodong Wang

Minimizing the nuclear norm of a matrix has been shown to be very efficient in reconstructing a low-rank sampled matrix. Furthermore, minimizing the sum of nuclear norms of matricizations of a tensor has been shown to be very efficient in recovering a low-Tucker-rank sampled tensor... (read more)

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