Code for the Weighted, Accelerated and Restarted Primal-dual algorithm. This algorithm achieves stable linear convergence for reconstruction from undersampled noisy measurements under an approximate sharpness condition. See the paper for details.

Related tags

Deep LearningWARPd
Overview

WARPd

Code for the Weighted, Accelerated and Restarted Primal-dual algorithm. This algorithm achieves stable linear convergence for reconstruction from undersampled noisy measurements under an approximate sharpness condition. See the paper for details.

The paper: "WARPd: A linearly convergent first-order method for inverse problems with approximate sharpness conditions"

Contents of code:

Main routines:
WARPd.m: main routine for the algorithm.
WARPdSR.m: noise-blind recovery version based on additional square-root LASSO term
WARPd_mc.m: version for matrix completion that uses PROPACK
WARPd_reweight.m and WARPdSR_reweight.m: iterative reweighting versions used for final numerical experiments

Example code of how to use main routines:
matrix_completion_example.m
shearlet_TVG_example.m

Owner
Matthew Colbrook
PhD student at DAMTP, University of Cambridge
Matthew Colbrook
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