Article Dans Une Revue Journal of Mathematical Imaging and Vision Année : 2017

Iterative Regularization via Dual Diagonal Descent

Résumé

In the context of linear inverse problems, we propose and study a general iterative regularization method allowing to consider large classes of regularizers and data-fit terms. The algorithm we propose is based on a primal-dual diagonal descent method. Our analysis establishes convergence as well as stability results. Theoretical findings are complemented with numerical experiments showing state of the art performances.

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hal-03886179 , version 1 (06-12-2022)

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Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa. Iterative Regularization via Dual Diagonal Descent. Journal of Mathematical Imaging and Vision, 2017, 60 (2), pp.189-215. ⟨10.1007/s10851-017-0754-0⟩. ⟨hal-03886179⟩
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