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Hauptverfasser: Boccacci, Patrizia, De Mol, Christine, Loris, Ignace
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2503.22523
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author Boccacci, Patrizia
De Mol, Christine
Loris, Ignace
author_facet Boccacci, Patrizia
De Mol, Christine
Loris, Ignace
contents In the framework of sparsity-enforcing regularisation for linear inverse problems, we consider the minimisation of a square-root Lasso cost function. To solve this problem we devise a simple modification (called SQRT-ISTA) of the Iterative Soft-Thresholding Algorithm (ISTA) for the Lasso problem and we prove convergence for this algorithm. Under some additional assumptions, we derive an upper bound on the convergence rate of the cost function. We also generalise these results to the case of the group square-root Lasso, where sparsity is enforced for groups of variables instead of individual ones.
format Preprint
id arxiv_https___arxiv_org_abs_2503_22523
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An iterative algorithm for the square-root Lasso
Boccacci, Patrizia
De Mol, Christine
Loris, Ignace
Optimization and Control
In the framework of sparsity-enforcing regularisation for linear inverse problems, we consider the minimisation of a square-root Lasso cost function. To solve this problem we devise a simple modification (called SQRT-ISTA) of the Iterative Soft-Thresholding Algorithm (ISTA) for the Lasso problem and we prove convergence for this algorithm. Under some additional assumptions, we derive an upper bound on the convergence rate of the cost function. We also generalise these results to the case of the group square-root Lasso, where sparsity is enforced for groups of variables instead of individual ones.
title An iterative algorithm for the square-root Lasso
topic Optimization and Control
url https://arxiv.org/abs/2503.22523