Causal Feature Selection for Algorithmic Fairness
Summary: Causal feature selection for fairness in data integration under a causal fairness framework, no predefined SCM required. Uses conditional independence tests over feature subsets, accelerated by group testing, with formal correctness and real-data evaluation. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sainyam Galhotra (University of Chicago)
- 2. Karthikeyan Shanmugam (IBM)
- 3. Prasanna Sattigeri (IBM)
- 4. Kush R. Varshney (IBM)
BibTeX Citation
@inproceedings{galhotra_sigmod22,
title = {{Causal Feature Selection for Algorithmic Fairness}},
author = {Galhotra, Sainyam and Shanmugam, Karthikeyan and Sattigeri, Prasanna and Varshney, Kush R.},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3517909},
url = {https://dl.acm.org/doi/10.1145/3514221.3517909},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,897 | Consistent Range Approximation for Fair Predictive Modeling | 2023 | VLDB | 5.6377501e-05 |
| 9,689 | FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data | 2023 | SIGMOD | 5.1258854e-05 |
| 9,990 | Fair and Actionable Causal Prescription Ruleset | 2025 | SIGMOD | 5.0845476e-05 |
| 10,076 | Maximizing Fair Content Spread via Edge Suggestion in Social Networks | 2022 | VLDB | 5.0732737e-05 |
| 10,531 | Fair Data Pre-Processing with Imperfect Attribute Space | 2026 | SIGMOD | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 656 | Materialization Optimizations for Feature Selection Workloads | 2014 | SIGMOD | 0.00015052106 |
| 783 | To Join or Not to Join? Thinking Twice about Joins before Feature Selection | 2016 | SIGMOD | 0.00014015599 |
| 804 | Interventional Fairness : Causal Database Repair for Algorithmic Fairness | 2019 | SIGMOD | 0.00013788292 |
| 2,097 | Open Data Integration | 2018 | VLDB | 9.0397587e-05 |
| 3,749 | Automated Feature Engineering for Algorithmic Fairness | 2021 | VLDB | 7.0348686e-05 |
| 7,555 | Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System | 2013 | VLDB | 5.4797204e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 13,817 | DENOUNCER: Detection of Unfairness in Classifiers | 2021 | VLDB |
| 2 | 6,897 | Consistent Range Approximation for Fair Predictive Modeling | 2023 | VLDB |
| 3 | 12,031 | Enforcing Constraints for Machine Learning Systems via Declarative Feature Selection: An Experimental Study | 2021 | SIGMOD |
| 4 | 1,954 | Interpretable Data-Based Explanations for Fairness Debugging | 2022 | SIGMOD |
| 5 | 10,531 | Fair Data Pre-Processing with Imperfect Attribute Space | 2026 | SIGMOD |
| 6 | 4,736 | OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning | 2021 | SIGMOD |
| 7 | 6,866 | Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification | 2022 | SIGMOD |
| 8 | 9,990 | Fair and Actionable Causal Prescription Ruleset | 2025 | SIGMOD |
| 9 | 804 | Interventional Fairness : Causal Database Repair for Algorithmic Fairness | 2019 | SIGMOD |
| 10 | 3,749 | Automated Feature Engineering for Algorithmic Fairness | 2021 | VLDB |