Linear Threshold for Oertel's Conjecture on the Mixed-Integer Volume
Hongyu Cheng, Amitabh Basu

TL;DR
This paper proves a linear threshold for Oertel's conjecture on mixed-integer convex sets, establishing new conditions under which a point with large halfspace depth exists, advancing understanding of volume distribution in such sets.
Contribution
It demonstrates that when the projection of the convex set contains an ball of radius proportional to the dimensions, Oertel's conjecture holds, extending previous results significantly.
Findings
Established a linear radius condition for the conjecture
Proved the conjecture for a larger family of sets than before
Showed the necessity of linear scaling for the radius condition
Abstract
Gr\"unbaum's inequality guarantees that the centroid of a convex body has halfspace depth at least : every halfspace containing the centroid captures at least a fraction of the body's volume. For mixed-integer convex sets where is a convex body, Oertel conjectured that there exists such that every closed halfspace containing satisfies , where denotes the -dimensional Hausdorff measure of . This conjecture is closely connected to complexity bounds for cutting plane methods and information complexity in mixed-integer convex optimization. Basu and Oertel established this conjecture for sets of sufficiently large lattice width, with the required lower bound on lattice width depending exponentially on the dimension. More recently, Cristi and Salas reduced this…
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Taxonomy
TopicsPoint processes and geometric inequalities · Computational Geometry and Mesh Generation · Complexity and Algorithms in Graphs
