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The Earth Mover’s Distance is a popular similarity measure in several branches of computer science. It measures the minimum total edge length of a perfect matching between two point sets. The Earth Mover’s Distance under Translation (EMDuT) is a translation-invariant version thereof. It minimizes the Earth Mover’s Distance over all translations of one point set.
For EMDuT in ℝ¹, we present an 𝒪̃(n²)-time algorithm. We also show that this algorithm is nearly optimal by presenting a matching conditional lower bound based on the Orthogonal Vectors Hypothesis. For EMDuT in ℝ^d, we present an 𝒪̃(n^{2d+2})-time algorithm for the L₁ and L_∞ metric. We show that this dependence on d is asymptotically tight, as an n^o(d)-time algorithm for L_1 or L_∞ would contradict the Exponential Time Hypothesis (ETH). Prior to our work, only approximation algorithms were known for these problems.
@InProceedings{bringmann_et_al:LIPIcs.SoCG.2024.25,
author = {Bringmann, Karl and Staals, Frank and W\k{e}grzycki, Karol and van Wordragen, Geert},
title = {{Fine-Grained Complexity of Earth Mover’s Distance Under Translation}},
booktitle = {40th International Symposium on Computational Geometry (SoCG 2024)},
pages = {25:1--25:17},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-316-4},
ISSN = {1868-8969},
year = {2024},
volume = {293},
editor = {Mulzer, Wolfgang and Phillips, Jeff M.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2024.25},
URN = {urn:nbn:de:0030-drops-199706},
doi = {10.4230/LIPIcs.SoCG.2024.25},
annote = {Keywords: Earth Mover’s Distance, Earth Mover’s Distance under Translation, Fine-Grained Complexity, Maximum Weight Bipartite Matching}
}