Determination of convex functions via subgradients of minimal norm

P Pérez-Aros, D Salas, E Vilches - Mathematical Programming, 2021 - Springer
Mathematical Programming, 2021Springer
We show, in Hilbert space setting, that any two convex proper lower semicontinuous
functions bounded from below, for which the norm of their minimal subgradients coincide,
they coincide up to a constant. Moreover, under classic boundary conditions, we provide the
same results when the functions are continuous and defined over an open convex domain.
These results show that for convex functions bounded from below, the slopes provide
sufficient first-order information to determine the function up to a constant, giving a positive …
Abstract
We show, in Hilbert space setting, that any two convex proper lower semicontinuous functions bounded from below, for which the norm of their minimal subgradients coincide, they coincide up to a constant. Moreover, under classic boundary conditions, we provide the same results when the functions are continuous and defined over an open convex domain. These results show that for convex functions bounded from below, the slopes provide sufficient first-order information to determine the function up to a constant, giving a positive answer to the conjecture posed in Boulmezaoud et al. (SIAM J Optim 28(3):2049–2066, 2018) .
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