We improve the space bound for streaming approximation of Diameter but also of Farthest Neighbor queries, Minimum Enclosing Ball and its Coreset, in high-dimensional Euclidean spaces. In particular, our deterministic streaming algorithms store 𝒪(ε^{-2}log(1/(ε))) points. This improves by a factor of ε^{-1} the previous space bound of Agarwal and Sharathkumar (SODA 2010), while retaining the state-of-the-art approximation guarantees, such as √2+ε for Diameter or Farthest Neighbor queries, and also offering a simpler and more complete argument. Moreover, we show that storing Ω(ε^{-1}) points is necessary for a streaming (√2+ε)-approximation of Farthest Pair and Farthest Neighbor queries.
@InProceedings{halldorsson_et_al:LIPIcs.ESA.2025.58, author = {Halld\'{o}rsson, Magn\'{u}s M. and Matsakis, Nicolaos and Vesel\'{y}, Pavel}, title = {{Streaming Diameter of High-Dimensional Points}}, booktitle = {33rd Annual European Symposium on Algorithms (ESA 2025)}, pages = {58:1--58:10}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-395-9}, ISSN = {1868-8969}, year = {2025}, volume = {351}, editor = {Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.58}, URN = {urn:nbn:de:0030-drops-245263}, doi = {10.4230/LIPIcs.ESA.2025.58}, annote = {Keywords: streaming algorithm, farthest pair, diameter, minimum enclosing ball, coreset} }
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