M. I. A. Ghitri, A. Hantoute

We use smoothing processes based on the infimal convolution of convex, proper and lower semi-continuous functions to regularize optimization problems given by means of non-convex composite functions. We show that the proposed approximations/regularization schemes still (epi-) converge to the original data, even if the chosen kernel is any convex function. This also allows for the derivation of upper estimates of the sub-differentials of the epi-limits of non-convex functions, without the use of qualifications (namely, BCQ-type conditions).

Keywords: Infimal convolution ⋅ Epi-convergence ⋅ Convex-composite function ⋅ Subdifferential ⋅ Deconvolution ⋅ Lower semi-continuous.


GT13.OPTCONT6 Invited Session
November 7, 2023  11:40 AM
CC1: Audience

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