- Documentation: https://friedlander.io/spgl1
SPGL1 is a Matlab solver for large-scale one-norm regularized least squares. It is designed to solve any of the following three problems:
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Basis pursuit denoise (BPDN): minimize ||x||_1 subject to ||Ax - b||_2 <= sigma,
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Basis pursuit (BP): minimize ||x||_1 subject to Ax = b
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Lasso: minimize ||Ax - b||_2 subject to ||x||_1 <= tau,
The matrix A can be defined explicily, or as an operator (i.e., a function) that return both both Ax and A'y. SPGL1 can solve these three problems in both the real and complex domains.
Home page: https://friedlander.io/spgl1
The algorithm implemented by SPGL1 is described in the paper
- E. van den Berg and M. P. Friedlander, "Probing the Pareto frontier for basis pursuit solutions", SIAM J. on Scientific Computing, 31(2):890-912, November 2008