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Statistics and Learning Theory in the Era of Artificial Intelligence

dc.date.accessioned2025-02-26T12:34:31Z
dc.date.available2025-02-26T12:34:31Z
dc.date.issued2024
dc.identifier.urihttp://publications.mfo.de/handle/mfo/4225
dc.description.abstractThe workshop highlighted recent theoretical advances on inference in high-dimensional statistical models based on the interplay of techniques from mathematical statistics, machine learning, theoretical computer science and related areas. The workshop brought together about 50 researchers in order to present new results, exchange ideas and explore open problems.
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.titleStatistics and Learning Theory in the Era of Artificial Intelligence
dc.rights.licenseUnless otherwise noted, the content of this report is licensed under Creative Commons Attribution-ShareAlike 4.0 International.*
dc.identifier.doi10.14760/OWR-2024-30
local.series.idOWR-2024-30
local.subject.msc68
local.date-range23 Jun - 28 Jun 2024
local.workshopcode2426
local.workshoptitleStatistics and Learning Theory in the Era of Artificial Intelligence
local.organizersFlorentina Bunea, Ithaca; Arnak Dalalyan, Palaiseau; Robert Nowak, Madison; Sara van de Geer, Zürich
local.report-nameWorkshop Report 2024,30
local.opc-photo-id2426
local.publishers-doi10.4171/OWR/2024/30


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