Low-Rank Tensor Decomposition over Finite Fields
Computational Complexity
2024-04-18 v4
Abstract
We show that finding rank- decompositions of a 3D tensor, for , over a fixed finite field can be done in polynomial time. However, if some cells in the tensor are allowed to have arbitrary values, then rank-2 is NP-hard over the integers modulo 2. We also explore rank-1 decomposition of a 3D tensor and of a matrix where some cells are allowed to have arbitrary values.
Cite
@article{arxiv.2401.06857,
title = {Low-Rank Tensor Decomposition over Finite Fields},
author = {Jason Yang},
journal= {arXiv preprint arXiv:2401.06857},
year = {2024}
}
Comments
12 pages, 0 figures; simpler solution for rank 4, shorter runtime analysis