2026-04-18T07:40:22Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/705212025-05-27T23:28:03Zcom_2072_6col_2072_452952

Mean estimation in high dimension Lugosi, Gábor Mean estimation Robustness High-dimensional statistics In this note we discuss the statistical problem of estimating the mean of a random vector based on independent, identically distributed data. This classical problem has recently attracted a lot of attention both in mathematical statistics and in theoretical computer science and numerous intricacies have been revealed. We discuss some of the recent advances, focusing on high-dimensional aspects. This work was supported by the Spanish Ministry of Economy and Competitiveness, Grant PGC2018-101643-B-I00 and by “Google Focused Award Algorithms and Learning for AI”. 2025-05-27T06:54:56Z 2025-05-27T06:54:56Z 2022 info:eu-repo/semantics/bookPart info:eu-repo/semantics/publishedVersion Lugosi G. Mean estimation in high dimension. In: Beliaev D, Smirnov S, editors. International Congress of Mathematicians: 2022 Jul 6-14. Berlin: International Mathematical Union; 2023. p. 5500-14. DOI: 10.4171/ICM2022/75 9783985470655 http://hdl.handle.net/10230/70521 http://dx.doi.org/10.4171/ICM2022/75 http://hdl.handle.net/10230/70521 eng Beliaev D, Smirnov S, editors. International Congress of Mathematicians: 2022 Jul 6-14. Berlin: International Mathematical Union; 2023. p. 5500-14 info:eu-repo/grantAgreement/ES/2PE/PGC2018-101643-B-I00 Published by EMS Press and licensed under a CC BY 4.0 license. http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess application/pdf application/pdf EMS Press