Persons
Jianhang Ai, MSc.
All publications
Hoeffding-Serfling Inequality for U-Statistics Without Replacement
- Authors: Jianhang Ai, MSc., Ing. Ondřej Kuželka, Ph.D., Wang, Y.
- Publication: JOURNAL OF THEORETICAL PROBABILITY. 2023, 36(1), 390-408. ISSN 0894-9840.
- Year: 2023
- DOI: 10.1007/s10959-022-01169-x
- Link: https://doi.org/10.1007/s10959-022-01169-x
- Department: Department of Computer Science, Intelligent Data Analysis
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Annotation:
Concentration inequalities quantify random fluctuations of functions of random variables, typically by bounding the probability that such a function differs from its expected value by more than a certain amount. In this paper we study one particular concentration inequality, the Hoeffding-Serfling inequality for U-statistics of random variables sampled without replacement from a finite set and extend recent results of Bardenet and Maillard (Bernoulli 21(3):1361-1385, 2015) to cover the U-statistics setting.
Hoeffding and Bernstein Inequalities for U-statistics without Replacement
- Authors: Jianhang Ai, MSc., Ing. Ondřej Kuželka, Ph.D., Wang, Y.
- Publication: Statistics and Probability Letters. 2022, 187 ISSN 0167-7152.
- Year: 2022
- DOI: 10.1016/j.spl.2022.109528
- Link: https://doi.org/10.1016/j.spl.2022.109528
- Department: Department of Computer Science, Intelligent Data Analysis
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Annotation:
Concentration inequalities quantify random fluctuations of functions of random variables, typically by bounding the probability that such a function differs from its expected value by more than a certain amount. In this paper, we extend Hoeffding’s inequality and Bernstein’s inequality for U-statistics to the setting of sampling without replacement from a finite population.
