mlsanityData to 7 Oct 2026

SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness

arXiv 2006.14168 ↗First posted 25 Jun 2020cs.LG stat.MLcited by 37

Not on the map. Why?

Abstract (arXiv)

In this paper, we cast fair machine learning as invariant machine learning. We first formulate a version of individual fairness that enforces invariance on certain sensitive sets. We then design a transport-based regularizer that enforces this version of individual fairness and develop an algorithm to minimize the regularizer efficiently. Our theoretical results guarantee the proposed approach trains certifiably fair ML models. Finally, in the experimental studies we demonstrate improved fairness metrics in comparison to several recent fair training procedures on three ML tasks that are susceptible to algorithmic bias.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Jun 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 6; 2022: 15; 2023: 10; 2024: 3; 2025: 2; 2026: 1.

37 papers.

Sort:

By area:

  1. 2021Towards Out-Of-Distribution Generalization: A Surveycited by 431
  2. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  3. 2023Fast Model Debias with Machine Unlearningcited by 70
  4. 2021Post-processing for Individual Fairnesscited by 61
  5. 2022FMP: Toward Fair Graph Message Passing against Topology Biascited by 35
  6. 2021Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimizationcited by 32
  7. 2021Latent Space Smoothing for Individually Fair Representationscited by 18
  8. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
  9. 2022CertiFair: A Framework for Certified Global Fairness of Neural Networkscited by 17
  10. 2022Accurate Fairness: Improving Individual Fairness without Trading Accuracycited by 16
  11. 2022Domain Adaptation meets Individual Fairness. And they get alongcited by 13
  12. 2021Individually Fair Gradient Boostingcited by 12
25 more
  1. 2023Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approachcited by 12
  2. 2023Chasing Fairness in Graphs: A GNN Architecture Perspectivecited by 12
  3. 2024AIM: Attributing, Interpreting, Mitigating Data Unfairnesscited by 9
  4. 2022Learning Antidote Data to Individual Unfairnesscited by 8
  5. 2021Individually Fair Rankingcited by 7
  6. 2023Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairnesscited by 7
  7. 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Toolscited by 7
  8. 2023GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hintcited by 6
  9. 2022iFlipper: Label Flipping for Individual Fairnesscited by 5
  10. 2022Human-Guided Fair Classification for Natural Language Processingcited by 5
  11. 2022Regulatory Instruments for Fair Personalized Pricingcited by 4
  12. 2022FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networkscited by 4
  13. 2023Retiring DeltaDP: New Distribution-Level Metrics for Demographic Paritycited by 4
  14. 2023Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spacescited by 4
  15. 2022SLIDE: a surrogate fairness constraint to ensure fairness consistencycited by 3
  16. 2024Monotone Individual Fairnesscited by 3
  17. 2022Outlier-Robust Group Inference via Gradient Space Clusteringcited by 2
  18. 2023Certification of Distributional Individual Fairnesscited by 2
  19. 2022fAux: Testing Individual Fairness via Gradient Alignmentcited by 1
  20. 2024Fairness Certification for Natural Language Processing and Large Language Modelscited by 1
  21. 2025Developing Fairness-Aware Task Decomposition to Improve Equity in Post-Spinal Fusion Complication Predictioncited by 1
  22. 2022Fair mappingcited by 0
  23. 2023Calibrated Data-Dependent Constraints with Exact Satisfaction Guaranteescited by 0
  24. 2025Wasserstein Distributionally Robust Optimization Through the Lens of Structural Causal Models and Individual Fairnesscited by 0
  25. 2026Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Studycited by 0