45 citations · 121 across the 21 of their papers we have counts for
6 papers · 1 filter
Sampling Rates for -Synthesis
Maximilian März, Claire Boyer, Jonas Kahn +1
This work investigates the problem of signal recovery from undersampled noisy sub-Gaussian measurements under the assumption of a synthesis-based sparsity model. Solving the $\ell^…
On oracle-type local recovery guarantees in compressed sensing
Ben Adcock, Claire Boyer, Simone Brugiapaglia
We present improved sampling complexity bounds for stable and robust sparse recovery in compressed sensing. Our unified analysis based on l1 minimization encompasses the case where…
Adapting to unknown noise level in sparse deconvolution
Claire Boyer, Yohann De Castro, Joseph Salmon
In this paper, we study sparse spike deconvolution over the space of complex-valued measures when the input measure is a finite sum of Dirac masses. We introduce a modified version…
Compressed sensing with structured sparsity and structured acquisition
Claire Boyer, Jérémie Bigot, Pierre Weiss
Compressed Sensing (CS) is an appealing framework for applications such as Magnetic Resonance Imaging (MRI). However, up-to-date, the sensing schemes suggested by CS theories are m…
An algorithm for variable density sampling with block-constrained acquisition
Claire Boyer, Pierre Weiss, Jérémie Bigot
Reducing acquisition time is of fundamental importance in various imaging modalities. The concept of variable density sampling provides a nice framework to achieve this. It was jus…
An analysis of block sampling strategies in compressed sensing
Jérémie Bigot, Claire Boyer, Pierre Weiss
Compressed sensing is a theory which guarantees the exact recovery of sparse signals from a small number of linear projections. The sampling schemes suggested by current compressed…