Statistics and Learning Theory in the Era of Artificial Intelligence

dc.date.accessioned	2025-02-26T12:34:31Z
dc.date.available	2025-02-26T12:34:31Z
dc.date.issued	2024
dc.identifier.uri	http://publications.mfo.de/handle/mfo/4225
dc.description.abstract	The 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.uri	http://creativecommons.org/licenses/by-sa/4.0/
dc.title	Statistics and Learning Theory in the Era of Artificial Intelligence
dc.rights.license	Unless otherwise noted, the content of this report is licensed under Creative Commons Attribution-ShareAlike 4.0 International.	*
dc.identifier.doi	10.14760/OWR-2024-30
local.series.id	OWR-2024-30
local.subject.msc	68
local.date-range	23 Jun - 28 Jun 2024
local.workshopcode	2426
local.workshoptitle	Statistics and Learning Theory in the Era of Artificial Intelligence
local.organizers	Florentina Bunea, Ithaca; Arnak Dalalyan, Palaiseau; Robert Nowak, Madison; Sara van de Geer, Zürich
local.report-name	Workshop Report 2024,30
local.opc-photo-id	2426
local.publishers-doi	10.4171/OWR/2024/30

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Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-sa/4.0/