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F3 KM: Federated, Fair, and Fast k-means

Summary: Federated, fair, and fast k-means (F3 KM): decomposes fair clustering into client-local ADMM subproblems with only updates exchanged. Supports multiple or no sensitive attributes; linear-time computation and favorable communication trade-offs; scales to 5M points in ~1 hour. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6805
Venue
SIGMOD
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,420 | 21.65%
DOI
10.1145/3626728

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{zhu_sigmod23,
        title = {{F3 KM: Federated, Fair, and Fast k-means}},
        author = {Zhu, Shengkun and Xu, Quanqing and Zeng, Jinshan and Wang, Sheng and Sun, Yuan and Yang, Zhifeng and Yang, Chuanhui and Peng, Zhiyong},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3626728},
        url = {https://dl.acm.org/doi/10.1145/3626728},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,615 Highly-Efficient Large-Scale k-means with Individual Fairness 2026 VLDB 5.093636e-05
10,959 Federated and Balanced Clustering for High-dimensional Data 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
291 OPTICS: Ordering Points To Identify the Clustering Structure 1999 SIGMOD 0.00022264197
364 Graph Clustering Based on Structural/Attribute Similarities 2009 VLDB 0.00020054172
1,579 k-Shape: Efficient and Accurate Clustering of Time Series 2015 SIGMOD 0.00010305183
1,597 Designing Fair Ranking Schemes 2019 SIGMOD 0.00010246472
1,937 Elastic Machine Learning Algorithms in Amazon SageMaker 2020 SIGMOD 9.4524758e-05
2,347 Vertica-ML: Distributed Machine Learning in Vertica Database 2020 SIGMOD 8.7157552e-05
2,562 Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies 2014 SIGMOD 8.4127196e-05
2,918 OceanBase: A 707 Million tpmC Distributed Relational Database System 2022 VLDB 7.9649716e-05
3,237 BlindFL: Vertical Federated Machine Learning without Peeking into Your Data 2022 SIGMOD 7.6089416e-05
4,057 On the Database/Network Interface in Large-Scale Publish/Subscribe Systems 2006 SIGMOD 6.9338609e-05
5,843 A Framework for Clustering Uncertain Data 2015 VLDB 6.068841e-05
6,353 Differentially Private Vertical Federated Clustering 2023 VLDB 5.9042628e-05
6,709 Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification 2022 SIGMOD 5.7964916e-05
7,360 On the Efficiency of K-Means Clustering: Evaluation, Optimization, and Algorithm Selection 2021 VLDB 5.6340845e-05
11,396 Prerequisite-driven Fair Clustering on Heterogeneous Information Networks 2023 SIGMOD 5.093636e-05
Previous Page 1 / 1 Next

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