13 citations · 15 across the 4 of their papers we have counts for
4 papers
Data-driven Distributionally Robust Optimization over Time
Kevin-Martin Aigner, Andreas Bärmann, Kristin Braun +5
Stochastic Optimization (SO) is a classical approach for optimization under uncertainty that typically requires knowledge about the probability distribution of uncertain parameters…
Set characterizations and convex extensions for geometric convex-hull proofs
Andreas Bärmann, Oskar Schneider
In the present work, we consider Zuckerberg's method for geometric convex-hull proofs introduced in [Geometric proofs for convex hull defining formulations, Operations Research Let…
The Bipartite Boolean Quadric Polytope with Multiple-Choice Constraints
Andreas Bärmann, Alexander Martin, Oskar Schneider
We consider the bipartite boolean quadric polytope (BQP) with multiple-choice constraints and analyse its combinatorial properties. The well-studied BQP is defined as the convex hu…
An Online-Learning Approach to Inverse Optimization
Andreas Bärmann, Alexander Martin, Sebastian Pokutta +1
In this paper, we demonstrate how to learn the objective function of a decision-maker while only observing the problem input data and the decision-maker's corresponding decisions o…