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.
| Original language | English |
|---|---|
| Pages (from-to) | 2498-2518 |
| Number of pages | 21 |
| Journal | Linear and Multilinear Algebra |
| Volume | 64 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 1 Dec 2016 |
Keywords
- optimisation
- random tensors
- rank-one tensors