Conjecture on the tensor-tubal-norm

Let a third-order tensor have a t-SVD with f-diagonal tensor S\boldsymbol{\mathscr{S}}, and define its tensor-tubal-rank as the number of nonzero diagonal tubes S(i,i,:)\boldsymbol{\mathscr{S}}(i,i,:). Define the tensor-tubal-norm (TTN) as the sum of the 2\ell_2 norms of these diagonal tubes. Tensor-tubal-norm conjecture. The tensor-tubal-norm is a norm and is the tightest convex relaxation of tensor-tubal-rank. This conjecture concerns a convex surrogate for tensor-tubal-rank, analogous to the nuclear norm as a convex relaxation of matrix rank. The source states that it is based on simulations and tests on a variety of cases, but provides no proof or resolution.

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Primary source

Zemin Zhang, Gregory Ely, Shuchin Aeron, Ning Hao and Misha Kilmer, “Novel Factorization Strategies for Higher Order Tensors: Implications for Compression and Recovery of Multi-linear Data”, arXiv:1307.0805 (2013).

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