Exponential Tilting of Subweibull Distributions
Abstract
The class of subweibull distributions has recently been shown to generalize the important properties of subexponential and subgaussian random variables. We describe alternative characterizations of subweibull distributions, illustrate their application to concentration inequalities, and detail the conditions under which their tail behavior is preserved after exponential tilting.
Cite
Text
Townes. "Exponential Tilting of Subweibull Distributions." Transactions on Machine Learning Research, 2025.Markdown
[Townes. "Exponential Tilting of Subweibull Distributions." Transactions on Machine Learning Research, 2025.](https://mlanthology.org/tmlr/2025/townes2025tmlr-exponential/)BibTeX
@article{townes2025tmlr-exponential,
title = {{Exponential Tilting of Subweibull Distributions}},
author = {Townes, F. William},
journal = {Transactions on Machine Learning Research},
year = {2025},
url = {https://mlanthology.org/tmlr/2025/townes2025tmlr-exponential/}
}