FairHash: A Fair and Memory/Time-efficient Hashmap

Summary: FairHash: data-dependent hashmap with group-level statistical parity across buckets, giving formal guarantees for three fairness notions. Three algorithmic families span zero/uniform unfairness vs. memory overhead, with ranking/cut/discrepancy trade-offs and near-baseline performance. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID: h52c0161c453f05c2
Venue: SIGMOD
Year: 2024
Pagerank: 4.9793485e-05
Overall Rank: 11,519 | 22.56%
DOI: 10.1145/3654939

Incoming Non-self Citations Over Time

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

Authors

1. Nima Shahbazi (University of Illinois Chicago)
2. Stavros Sintos (University of Illinois Chicago)
3. Abolfazl Asudeh (University of Illinois Chicago)

BibTeX Citation

@inproceedings{shahbazi_sigmod24,
        title = {{FairHash: A Fair and Memory/Time-efficient Hashmap}},
        author = {Shahbazi, Nima and Sintos, Stavros and Asudeh, Abolfazl},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3654939},
        url = {https://dl.acm.org/doi/10.1145/3654939},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,453	Fair-Count-Min: Frequency Estimation under Equal Group-wise Approximation Factor	2026	SIGMOD	4.9793485e-05
10,696	On Fair Epsilon Net and Geometric Hitting Set	2026	VLDB	4.9793485e-05
10,811	Unbiased Binning for Fairness-aware Attribute Representation	2026	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
40	The Case for Learned Index Structures	2018	SIGMOD	0.00046284649
803	Interventional Fairness : Causal Database Repair for Algorithmic Fairness	2019	SIGMOD	0.00013836858
848	Benchmarking Learned Indexes	2021	VLDB	0.00013506188
1,162	Responsible Data Management	2020	VLDB	0.00011753159
1,379	Designing Fair Ranking Schemes	2019	SIGMOD	0.0001086418
3,690	Fair Near Neighbor Search: Independent Range Sampling in High Dimensions	2020	PODS	7.0936701e-05
4,890	Can Learned Models Replace Hash Functions?	2023	VLDB	6.3682031e-05
5,609	Responsible Data Integration: Next-generation Challenges	2022	SIGMOD	6.0689501e-05
5,610	On Obtaining Stable Rankings	2019	VLDB	6.0686149e-05
5,738	Tailoring Data Source Distributions for Fairness-aware Data Integration	2021	VLDB	6.0117538e-05
7,489	Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes	2021	SIGMOD	5.5113546e-05
9,091	MithraRanking: A System for Responsible Ranking Design	2019	SIGMOD	5.2283159e-05
10,032	Maximizing Fair Content Spread via Edge Suggestion in Social Networks	2022	VLDB	5.0925155e-05

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9	3,690	Fair Near Neighbor Search: Independent Range Sampling in High Dimensions	2020	PODS
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