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UID:403@cran.univ-lorraine.fr
DTSTART;TZID=Europe/Paris:20240325T140000
DTEND;TZID=Europe/Paris:20240325T150000
DTSTAMP:20240414T180043Z
URL:https://www.cran.univ-lorraine.fr/events/seminaire-paul-catala/
SUMMARY:Séminaire Paul Catala
DESCRIPTION:Speaker: Paul Catala (Helmholtz Munich\, TUM\, Germany)\nTitle:
  An Approximate Joint Diagonalization Algorithm for Off-the-Grid Sparse Re
 covery\n\nMany problems in imaging and data science require to reconstruct
 \, from partial observations\, highly concentrated signals\, such as point
 wise sources or contour lines. This work introduces a novel algorithm for 
 recovering measures supported on such structured domains\, given a finite 
 number of their moments. Our approach is based on the traditional singular
  value decomposition methodology of subspace methods\, but lifts their res
 triction to the framework of Dirac masses\, and is able to recover geometr
 ically faithful discrete approximations of measures with density. The cruc
 ial step consists in the approximate joint diagonalization of a few non-co
 mmuting matrices\, which we perform using a quasi-Newton algorithm. Experi
 ments show that our method performs well\, not only in the setting of well
  separated Dirac masses\, as predicted by the standard theory of the trunc
 ated moment problem\, but also in the case of continuous measures\, which 
 is not covered by theoretical guarantees and where usual methods empirical
 ly fail. We illustrate its applicability in optimal transport problems\, w
 here the coupling measure is often localized on the graph of some function
 .
CATEGORIES:Département BioSiS,Séminaires projet SiMul
LOCATION:CRAN - FST - 4ème\, Campus Sciences\, Boulevard des Aiguillettes\
 , Vandoeuvre-lès-Nancy\, 54506\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Campus Sciences\, Boulevard
  des Aiguillettes\, Vandoeuvre-lès-Nancy\, 54506\, France;X-APPLE-RADIUS=
 100;X-TITLE=CRAN - FST - 4ème:geo:0,0
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DTSTART:20231029T020000
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