704 citations · 3.6k across the 98 of their papers we have counts for
6 papers · 1 filter
Efficient Least Residual Greedy Algorithms for Sparse Recovery
Guy Leibovitz, Raja Giryes
We present a novel stagewise strategy for improving greedy algorithms for sparse recovery. We demonstrate its efficiency both for synthesis and analysis sparse priors, where in bot…
Generalizing CoSaMP to Signals from a Union of Low Dimensional Linear Subspaces
Tom Tirer, Raja Giryes
The idea that signals reside in a union of low dimensional subspaces subsumes many low dimensional models that have been used extensively in the recent decade in many fields and ap…
Tradeoffs between Convergence Speed and Reconstruction Accuracy in Inverse Problems
Raja Giryes, Yonina C. Eldar, Alex M. Bronstein +1
Solving inverse problems with iterative algorithms is popular, especially for large data. Due to time constraints, the number of possible iterations is usually limited, potentially…
Near Oracle Performance and Block Analysis of Signal Space Greedy Methods
Raja Giryes, Deanna Needell
Compressive sampling (CoSa) is a new methodology which demonstrates that sparse signals can be recovered from a small number of linear measurements. Greedy algorithms like CoSaMP h…
A Greedy Algorithm for the Analysis Transform Domain
Raja Giryes
Many image processing applications benefited remarkably from the theory of sparsity. One model of sparsity is the cosparse analysis one. It was shown that using l_1-minimization on…
Greedy Signal Space Methods for incoherence and beyond
Raja Giryes, Deanna Needell
Compressive sampling (CoSa) has provided many methods for signal recovery of signals compressible with respect to an orthonormal basis. However, modern applications have sparked th…