The converse characterization of convex Lipschitzian functions

Let XX be the domain of a Lipschitzian function F:XRF:X\to\mathbb{R}, and let F(x)\nabla F(\boldsymbol{x}) denote the set of subgradients of FF at x\boldsymbol{x}. For x,yX\boldsymbol{x},\boldsymbol{y}\in X and 0t10\leq t\leq 1, assume that F(x)F(y)\nabla F(\boldsymbol{x})\cap\nabla F(\boldsymbol{y})\neq\varnothing. Convexity characterization. The function FF is convex if and only if

F(x)F(y)=F(tx+(1t)y).\nabla F(\boldsymbol{x})\cap\nabla F(\boldsymbol{y})=\nabla F(t\boldsymbol{x}+(1-t)\boldsymbol{y}).

This is proposed as the converse of the preceding convexity property for subgradient sets; the supplied text does not state whether the characterization has been proved or remains open.

Sources & referencesView supporting material

Primary source

Jürgen Jost and Dong Zhang, “Discrete-to-Continuous Extensions: piecewise multilinear extension, min-max theory and spectral theory”, arXiv:2106.04116 (2021).

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