mlsanityData to 14 Oct 2026

A Short Note on Concentration Inequalities for Random Vectors with SubGaussian Norm

arXiv 1902.03736 ↗First posted 11 Feb 2019math.PR cs.LG stat.MLcited by 106

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Abstract (arXiv)

In this note, we derive concentration inequalities for random vectors with subGaussian norm (a generalization of both subGaussian random vectors and norm bounded random vectors), which are tight up to logarithmic factors.

Key facts. Cited by 106 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Feb 2019.

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Citing papers per year: 2021: 17; 2022: 18; 2023: 28; 2024: 21; 2025: 17; 2026: 5.

106 papers.

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  11. 2024A Unified Confidence Sequence for Generalized Linear Models, with Applications to Banditscited by 29
  12. 2023Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noisecited by 26
38 more
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