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cs.DS2026

An Approximation Algorithm for Graph Label Selection

Josia John, Simon Meierhans, Maximilian Probst Gutenberg

In the graph label selection problem, one is given an -vertex graph and a budget , and seeks to select vertices whose labels enable accurate prediction of the labels on t…

cs.DS2025

Dynamic Connectivity with Expected Polylogarithmic Worst-Case Update Time

Simon Meierhans, Maximilian Probst Gutenberg

Whether a graph is connected is arguably its most fundamental property. Naturally, connectivity was the first characteristic studied for dynamic graphs, i.e. graphs that…

cs.DS2025

Expander Pruning with Polylogarithmic Worst-Case Recourse and Update Time

Simon Meierhans, Maximilian Probst Gutenberg, Thatchaphol Saranurak

Expander graphs are known to be robust to edge deletions in the following sense: for any online sequence of edge deletions to an -edge graph that is…

cs.DS2025

Parallel and Distributed Expander Decomposition: Simple, Fast, and Near-Optimal

Daoyuan Chen, Simon Meierhans, Maximilian Probst Gutenberg +1

Expander decompositions have become one of the central frameworks in the design of fast algorithms. For an undirected graph , a near-optimal -expander decomposition is…

cs.DS2024

Bootstrapping Dynamic APSP via Sparsification

Rasmus Kyng, Simon Meierhans, Gernot Zöcklein

We give a simple algorithm for the dynamic approximate All-Pairs Shortest Paths (APSP) problem. Given a graph with polynomially bounded edge lengths, our data struc…

cs.DS2024

A Simple Dynamic Spanner via APSP

Rasmus Kyng, Simon Meierhans, Gernot Zöcklein

We give a simple algorithm for maintaining a -approximate spanner of a graph with vertices as receives edge updates by reduction to the dynamic All-Pairs…