Gaussian differentially private robust mean estimation and inference-Reference-Cited by-同舟云学术

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Gaussian differentially private robust mean estimation and inference

Published:2024-11-01 Issue:4 Volume:30 Page:
ISSN:1350-7265
Container-title:Bernoulli
language:
Short-container-title:Bernoulli

Author:

Yu Myeonghun¹,Ren Zhao²,Zhou Wen-Xin³

Affiliation:

1. Department of Mathematics, University of California, San Diego, La Jolla, CA, 92093, USA

2. Department of Statistics, University of Pittsburgh, Pittsburgh, PA, 15260, USA

3. Department of Information and Decision Sciences, University of Illinois at Chicago, Chicago, IL, 60607, USA

Publisher

Bernoulli Society for Mathematical Statistics and Probability

Reference58 articles.

1. Vershynin, R. (2018). High-Dimensional Probability: An Introduction with Applications in Data Science. Cambridge Series in Statistical and Probabilistic Mathematics 47. Cambridge: Cambridge Univ. Press. 10.1017/9781108231596

2. Catoni, O. (2012). Challenging the empirical mean and empirical variance: A deviation study. Ann. Inst. Henri Poincaré Probab. Stat. 48 1148–1185. 10.1214/11-AIHP454

3. Fan, J., Li, Q. and Wang, Y. (2017). Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions. J. R. Stat. Soc. Ser. B. Stat. Methodol. 79 247–265. 10.1111/rssb.12166

4. Huber, P.J. (1964). Robust estimation of a location parameter. Ann. Math. Stat. 35 73–101. 10.1214/aoms/1177703732

5. Minsker, S. (2015). Geometric median and robust estimation in Banach spaces. Bernoulli 21 2308–2335. 10.3150/14-BEJ645

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