Approximate Selection with Unreliable Comparisons in Optimal Expected Time. - Shengyu Huang; Chih-Hung Liu 001; Daniel Rutschmann (STACS, 2023)

Triangulations Admit Dominating Sets of Size 2n/7. - Aleksander B. G. Christiansen; Eva Rotenberg; Daniel Rutschmann (CoRR, 2023)

Chains, Koch Chains, and Point Sets with Many Triangulations. - Daniel Rutschmann; Manuel Wettstein (J. ACM, 2023)

Tight Bounds for Sorting Under Partial Information. - Ivor van der Hoog; Daniel Rutschmann (FOCS, 2024)

Triangulations Admit Dominating Sets of Size 2n/7. - Aleksander B. G. Christiansen; Eva Rotenberg; Daniel Rutschmann (SODA, 2024)

Efficient Greedy Discrete Subtrajectory Clustering. - Ivor van der Hoog; Lara Ost; Eva Rotenberg; Daniel Rutschmann (SoCG, 2025)

Simpler Optimal Sorting from a Directed Acyclic Graph. - Ivor van der Hoog; Eva Rotenberg; Daniel Rutschmann (SOSA, 2025)

Instance-Optimal Imprecise Convex Hull. - Sarita de Berg; Ivor van der Hoog; Eva Rotenberg; Daniel Rutschmann; Sampson Wong (CoRR, 2025)

Simple Universally Optimal Dijkstra. - Ivor van der Hoog; Eva Rotenberg; Daniel Rutschmann (CoRR, 2025)

A Combinatorial Proof of Universal Optimality for Computing a Planar Convex Hull. - Ivor van der Hoog; Eva Rotenberg; Daniel Rutschmann (CoRR, 2025)

Approximate selection with unreliable comparisons in sublinear time. - Shengyu Huang; Chih-Hung Liu 001; Daniel Rutschmann (J. Comput. Syst. Sci., 2026)