G-2016-12
Algorithmic construction of the subdifferential from directional derivatives
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The subdifferential of a function is a generalization for nonsmooth functions of the concept of gradient. It is frequently used in variational analysis, particularly in the context of nonsmooth optimization. The present work proposes algorithms to reconstruct a polyhedral subdifferential of a function from the computation of finitely many directional derivatives. We provide upper bounds on the required number of directional derivatives when the space is \(\mathbb{R}^1\)
and \(\mathbb{R}^2\)
, as well as in \(\mathbb{R}^n\)
where subdifferential is known to possess at most three vertices.
Paru en février 2016 , 20 pages
Axe de recherche
Publication
sept. 2018
et
Set-Valued and Variational Analysis, 26(3), 431–447, 2018
référence BibTeX