  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 formulas that
relates this average to problems in random matrix theory.
