Optimal fiber comparisons for random tensors

We extend Seginer's matrix norm comparison to tensors with optimal dependence on the tensor order. For a real tensor $T$ of order $k\ge2$ with centered, integrable, independent and identically distributed entries, we prove $\mathbb{E} f(T)\le\mathbb{E}\lVert T\rVert_{\mathrm{inj}} \le C\sqrt{k\log k}\,\mathbb{E} f(T)$, where $f(T)$ is the largest Euclidean norm of a one-dimensional fiber and $C$ is universal. The comparison holds for every finite rectangular format, and the entry law may depend on both the dimensions and the tensor order. We show that the factor $\sqrt{k\log k}$ is optimal by considering Rademacher tensors on $[2]^k$.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-29
DOI
https://doi.org/10.48550/arxiv.2610.39389
Primary Topic
Tensor decomposition and applications
Type
preprint
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preprint

Optimal fiber comparisons for random tensors

Huangang Lu, Ziqian Lin
arXiv (Cornell University)
Tensor decomposition and applications
preprint

Optimal fiber comparisons for random tensors

Huangang Lu, Ziqian Lin
preprint en

Abstract

We extend Seginer's matrix norm comparison to tensors with optimal dependence on the tensor order. For a real tensor $T$ of order $k\ge2$ with centered, integrable, independent and identically distributed entries, we prove $\mathbb{E} f(T)\le\mathbb{E}\lVert T\rVert_{\mathrm{inj}} \le C\sqrt{k\log k}\,\mathbb{E} f(T)$, where $f(T)$ is the largest Euclidean norm of a one-dimensional fiber and $C$ is universal. The comparison holds for every finite rectangular format, and the entry law may depend on both the dimensions and the tensor order. We show that the factor $\sqrt{k\log k}$ is optimal by considering Rademacher tensors on $[2]^k$.

arXiv (Cornell University)
Tensor decomposition and applications
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Optimal fiber comparisons for random tensors — Huangang Lu, Ziqian Lin · arXiv (Cornell University) (2026) | TGRS Research Map | TGRS