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arXiv · 1610.02170

Iterative regularization via dual diagonal descent

Guillaume Garrigos·Lorenzo Rosasco·Silvia Villa
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Abstract

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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Guillaume Garrigos, Lorenzo Rosasco, Silvia Villa. 2016-10-07. Iterative regularization via dual diagonal descent. https://doi.org/10.1007/s10851-017-0754-0

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