Abstract
Motivated by the many potential applications of low-rank multi-way tensor approximations, we set out to count the rank-one tensors that are critical points of the distance function to a general tensor v. As this count depends on v, we average over v drawn from a Gaussian distribution, and find a formula that relates this average to problems in random matrix theory.
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Draisma, J., & Horobeţ, E. (2016). The average number of critical rank-one approximations to a tensor. Linear and Multilinear Algebra, 64(12), 2498–2518. https://doi.org/10.1080/03081087.2016.1164660
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