Computing the Gromov-Hausdorff Distance for Metric Trees

被引:8
|
作者
Agarwal, Pankaj K. [1 ]
Fox, Kyle [2 ]
Nath, Abhinandan [1 ]
Sidiropoulos, Anastasios [3 ]
Wang, Yusu [4 ]
机构
[1] Duke Univ, Levine Sci Res Ctr, Dept Comp Sci, Box 90129, Durham, NC 27708 USA
[2] Univ Texas Dallas, Dept Comp Sci, 800 W Campbell Rd,MS EC-31, Richardson, TX 75080 USA
[3] Univ Illinois, 851 S Morgan St,Room 1240 SEO, Chicago, IL 60607 USA
[4] Ohio State Univ, Comp Sci & Engn Dept, Dreese Lab 487, 2015 Neil Ave, Columbus, OH 43210 USA
关键词
Metric spaces; embeddings;
D O I
10.1145/3185466
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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 GH 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(min{n, root 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(root n)-approximation algorithm.
引用
收藏
页数:20
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