Mean estimation in high dimension
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- dc.contributor.author Lugosi, Gábor
- dc.date.accessioned 2025-05-27T06:54:56Z
- dc.date.available 2025-05-27T06:54:56Z
- dc.date.issued 2022
- dc.description.abstract 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.en
- dc.description.sponsorship 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”.en
- dc.format.mimetype application/pdf
- dc.identifier.citation 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
- dc.identifier.doi http://dx.doi.org/10.4171/ICM2022/75
- dc.identifier.isbn 9783985470655
- dc.identifier.uri http://hdl.handle.net/10230/70521
- dc.language.iso eng
- dc.publisher EMS Press
- dc.relation.ispartof Beliaev D, Smirnov S, editors. International Congress of Mathematicians: 2022 Jul 6-14. Berlin: International Mathematical Union; 2023. p. 5500-14
- dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-101643-B-I00
- dc.rights Published by EMS Press and licensed under a CC BY 4.0 license.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Mean estimationen
- dc.subject.keyword Robustnessen
- dc.subject.keyword High-dimensional statisticsen
- dc.title Mean estimation in high dimensionen
- dc.type info:eu-repo/semantics/bookPart
- dc.type.version info:eu-repo/semantics/publishedVersion