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Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering*

Summary: Fast parallel EMST and HDBSCAN* via WSPD-based Kruskal and bichromatic closest pairs. A new well-separation reduces work; parallel divide-and-conquer builds dendrograms and reachability with compact WSP subsets, delivering speedups over serial and prior parallel methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h77dfb80649545af4
Venue
SIGMOD
Year
2021
Pagerank
4.9793485e-05
Overall Rank
11,982 | 19.44%
DOI
10.1145/3448016.3457296

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Authors

BibTeX Citation

@inproceedings{wang_sigmod21,
        title = {{Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering*}},
        author = {Wang, Yiqiu and Yu, Shangdi and Gu, Yan and Shun, Julian},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457296},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457296},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
11,115 Parallel kd-tree with Batch Updates 2025 SIGMOD 4.9793485e-05
11,889 ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain 2022 VLDB 4.9793485e-05
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