mlsanityData to 7 Oct 2026

Computing the Gromov-Hausdorff Distance for Metric Trees

arXiv 1509.05751 ↗First posted 18 Sep 2015cs.CGcited by 4

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Abstract (arXiv)

The Gromov-Hausdorff (GH) distance is a natural way to measure distance between two metric spaces. We prove that it is NP-hard to approximate the Gromov-Hausdorff distance better than a factor of 3 for geodesic metrics on a pair of trees. We complement this result by providing a polynomial time O(minn, √rn)-approximation algorithm for computing the GH distance between a pair of metric trees, where r is the ratio of the longest edge length in both trees to the shortest edge length. For metric trees with unit length edges, this yields an O(√n)-approximation algorithm.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Sep 2015.

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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 2; 2025: 0; 2026: 1.

4 papers.