Corpus ID: 204837870

# Deterministic tensor completion with hypergraph expanders

```@article{Harris2019DeterministicTC,
title={Deterministic tensor completion with hypergraph expanders},
author={K. D. Harris and Yizhe Zhu},
journal={ArXiv},
year={2019},
volume={abs/1910.10692}
}```
• Published 2019
• Mathematics, Computer Science
• ArXiv
We provide a novel analysis of low rank tensor completion based on hypergraph expanders. As a proxy for rank, we minimize the max-quasinorm of the tensor, introduced by Ghadermarzy, Plan, and Yilmaz (2018), which generalizes the max-norm for matrices. Our analysis is deterministic and shows that the number of samples required to recover an order-\$t\$ tensor with at most \$n\$ entries per dimension is linear in \$n\$, under the assumption that the rank and order of the tensor are \$O(1)\$. As steps in… Expand
3 Citations

#### Figures from this paper

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