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arXiv · 2303.14021

Forward-Backward algorithms for weakly convex problems

Ewa Bednarczuk·Giovanni Bruccola·Gabriele Scrivanti·The Hung Tran
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Abstract

We investigate the convergence properties of exact and inexact forward-backward algorithms to minimise the sum of two weakly convex functions defined on a Hilbert space, where one has a Lipschitz-continuous gradient. We show that the exact forward-backward algorithm converges strongly to a global solution, provided that the objective function satisfies a sharpness condition. For the inexact forward-backward algorithm, the same condition ensures that the distance from the iterates to the solution set approaches a positive threshold depending on the accuracy level of the proximal computations. As an application of the considered setting, we provide numerical experiments related to discrete tomography.

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Ewa Bednarczuk, Giovanni Bruccola, Gabriele Scrivanti, The Hung Tran. 2023-03-24. Forward-Backward algorithms for weakly convex problems. https://arxiv.org/abs/2303.14021

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