On Diameter Approximation in Directed Graphs
Amir Abboud, Mina Dalirrooyfard, Ray Li, Virginia Vassilevska-Williams

TL;DR
This paper advances the understanding of diameter approximation in directed graphs by introducing a faster algorithm with better approximation and establishing new complexity lower bounds that differ from undirected cases.
Contribution
It presents the first subquadratic algorithm for sparse directed graph diameter with improved approximation, and introduces new hardness reductions separating roundtrip and directed diameters.
Findings
First algorithm for diameter in sparse directed graphs with subquadratic time and better than 2-approximation.
New hardness reductions for roundtrip diameter, refuting certain approximation possibilities under specific hypotheses.
Establishes that some diameter approximation improvements would imply breakthroughs in other computational problems.
Abstract
Computing the diameter of a graph, i.e. the largest distance, is a fundamental problem that is central in fine-grained complexity. In undirected graphs, the Strong Exponential Time Hypothesis (SETH) yields a lower bound on the time vs. approximation trade-off that is quite close to the upper bounds. In \emph{directed} graphs, however, where only some of the upper bounds apply, much larger gaps remain. Since may not be the same as , there are multiple ways to define the problem, the two most natural being the \emph{(one-way) diameter} () and the \emph{roundtrip diameter} (). In this paper we make progress on the outstanding open question for each of them. -- We design the first algorithm for diameter in sparse directed graphs to achieve time with an approximation factor better than . The new…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
