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)
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Authors
- 1. Yiqiu Wang
- 2. Shangdi Yu
- 3. Yan Gu
- 4. Julian Shun
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,398 | Parallel kd-tree with Batch Updates | 2025 | SIGMOD | 4.1905499e-05 |
| 11,385 | ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain | 2022 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 263 | OPTICS: Ordering Points To Identify the Clustering Structure | 1999 | SIGMOD | 0.00029955858 |
| 2,669 | NG-DBSCAN: Scalable Density-Based Clustering for Arbitrary Data | 2017 | VLDB | 8.3429208e-05 |
| 3,296 | RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning | 2018 | SIGMOD | 7.2553154e-05 |
| 5,417 | Theoretically-Efficient and Practical Parallel DBSCAN | 2020 | SIGMOD | 5.5162242e-05 |
| 5,827 | Fast Euclidean OPTICS with Bounded Precision in Low Dimensional Space | 2018 | SIGMOD | 5.3111132e-05 |
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