Show simple item record

Applied Harmonic Analysis and Data Science

dc.date.accessioned2025-02-26T12:31:31Z
dc.date.available2025-02-26T12:31:31Z
dc.date.issued2024
dc.identifier.urihttp://publications.mfo.de/handle/mfo/4216
dc.description.abstractData science is a field of major importance for science and technology nowadays and poses a large variety of challenging mathematical questions. The area of applied harmonic analysis has a significant impact on such problems by providing methodologies both for theoretical questions and for a wide range of applications in machine learning, as well as in in signal and image processing. Building on the success of four previous workshops on applied harmonic analysis in 2012, 2015, 2018, 2021, this workshop focused on several exciting directions, such as mathematical theory of deep learning, phase-retrieval time-frequency analysis, and sampling on t-design curves, and discussed open problems in the field.
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.titleApplied Harmonic Analysis and Data Science
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-2024-21
local.series.idOWR-2024-21
local.subject.msc94
local.subject.msc68
local.subject.msc42
local.subject.msc08
local.subject.msc65
local.date-range21 Apr - 26 Apr 2024
local.workshopcode2417
local.workshoptitleApplied Harmonic Analysis and Data Science
local.organizersIngrid Daubechies, Durham; Gitta Kutyniok, München; Holger Rauhut, Aachen
local.report-nameWorkshop Report 2024,21
local.opc-photo-id2417
local.publishers-doi10.4171/OWR/2024/21


Files in this item

Thumbnail
Report

This item appears in the following Collection(s)

Show simple item record

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