Local Search Methods for k-Means with Outliers
Summary: Proposes a simple local-search algorithm for k-means with outliers, delivering constant-factor guarantees for the inlier clustering. When paired with sketching techniques, it scales to large data and empirically dominates recent heuristics on synthetic and real-world benchmarks. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shalmoli Gupta
- 2. Ravi Kumar
- 3. Kefu Lu
- 4. Benjamin Moseley
- 5. Sergei Vassilvitskii
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,469 | Fast Density-Peaks Clustering: Multicore-based Parallelization Approach | 2021 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 159 | LOF: Identifying Density-Based Local Outliers | 2000 | SIGMOD | 0.00040135453 |
| 340 | CURE: An Efficient Clustering Algorithm for Large Databases | 1998 | SIGMOD | 0.00026854084 |
| 697 | Efficient Algorithms for Mining Outliers from Large Data Sets | 2000 | SIGMOD | 0.00017964755 |
| 768 | Algorithms for Mining Distance-Based Outliers in Large Datasets | 1998 | VLDB | 0.00016864875 |
| 1,375 | SQLEM: Fast Clustering in SQL using the EM Algorithm | 2000 | SIGMOD | 0.00012321024 |
| 2,146 | Scalable K-Means++ | 2012 | VLDB | 9.4341455e-05 |
| 2,826 | Finding Intensional Knowledge of Distance-Based Outliers | 1999 | VLDB | 8.0562807e-05 |
| 4,549 | Outlier Detection for High Dimensional Data | 2001 | SIGMOD | 6.0866685e-05 |
| 5,768 | Outlier-robust Clustering using Independent Components | 2008 | SIGMOD | 5.3332593e-05 |
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