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Sharp Concentration of Simple Random Tensors

Probability 2025-09-30 v2 Statistics Theory Statistics Theory

Abstract

This paper establishes sharp dimension-free concentration inequalities and expectation bounds for the deviation of the sum of simple random tensors from its expectation. As part of our analysis, we use generic chaining techniques to obtain a sharp high-probability upper bound on the suprema of LpL_p empirical processes. In so doing, we generalize classical results for quadratic and product empirical processes to higher-order settings.

Keywords

Cite

@article{arxiv.2502.16916,
  title  = {Sharp Concentration of Simple Random Tensors},
  author = {Omar Al-Ghattas and Jiaheng Chen and Daniel Sanz-Alonso},
  journal= {arXiv preprint arXiv:2502.16916},
  year   = {2025}
}

Comments

36 pages, minor revision, to appear in Information and Inference

R2 v1 2026-06-28T21:55:06.987Z