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SUMMARY:On the gap between local recovery guarantees in structured compres
 sed sensing and oracle estimates - Claire Boyer (UPMC)
DTSTART:20180302T140000Z
DTEND:20180302T150000Z
UID:TALK98683@talks.cam.ac.uk
CONTACT:Quentin Berthet
DESCRIPTION:First we will introduce a compressed sensing (CS) theory more 
 compatible with real-life applications: we derive guarantees to ensure rec
 onstruction of a structured sparse signal of interest while imposing struc
 ture in the acquisition (no Gaussian measurements here...). We will study 
 how far those CS results are from oracle-type guarantees\, and we will sho
 w that they are similar in terms of the required number of measurements. T
 hese results give an insight to design new optimal sampling strategies whe
 n realistic physical constraints are imposed in the acquisition.\nSecondly
 \, we will present some generation of sampling patterns in MRI\, consistin
 g in projecting a density onto a set of admissible measures.\n
LOCATION:MR12
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