This toolbox contains the implementation of what I consider to be fundamental algorithms
for non-smooth convex optimization of structured functions. These algorithms might not be the fasted
(although they certainly are quite efficient), but they all have a simple implementation in term
of black boxes (gradient and proximal mappings, given as callbacks). However, you should have
some knowledge about what is a gradient operator and a proximal mapping in order to be able
to use this toolbox on your own problems. I suggest you have a look at the
"suggested readings" for some more information about all this.
Gabriel Peyre (2022). Toolbox Sparse Optmization (https://www.mathworks.com/matlabcentral/fileexchange/16204-toolbox-sparse-optmization), MATLAB Central File Exchange. Retrieved .
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Inspired: CoSaMP and OMP for sparse recovery
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