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math.OC2026
A Safe Approximation Based on Mixed-Integer Optimization for Non-Convex Distributional Robustness Governed by Univariate Indicator Functions
Jana Dienstbier, Frauke Liers, Florian Rösel +1
In this work, we present an algorithmically tractable safe approximation of distributionally robust optimization (DRO) problems that contain univariate indicator functions. The lat…
math.OC2025
A Positive Semidefinite Safe Approximation of Multivariate Distributionally Robust Constraints Determined by Simple Functions
J. Dienstbier, F. Liers, J. Rolfes
Single-level reformulations of (non-convex) distributionally robust optimization (DRO) problems are often intractable, as they contain semiinfinite dual constraints. Based on such…
math.OC2025
A semidefinite programming hierarchy for covering problems in discrete geometry
Cordian Riener, Jan Rolfes, Frank Vallentin
In this paper we present a new semidefinite programming hierarchy for covering problems in compact metric spaces. Over the last years, these kind of hierarchies were developed prim…