mlsanityData to 7 Oct 2026

Bias Mitigation Post-processing for Individual and Group Fairness

arXiv 1812.06135 ↗First posted 14 Dec 2018cs.LG cs.CY stat.MLcited by 72

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Abstract (arXiv)

Whereas previous post-processing approaches for increasing the fairness of predictions of biased classifiers address only group fairness, we propose a method for increasing both individual and group fairness. Our novel framework includes an individual bias detector used to prioritize data samples in a bias mitigation algorithm aiming to improve the group fairness measure of disparate impact. We show superior performance to previous work in the combination of classification accuracy, individual fairness and group fairness on several real-world datasets in applications such as credit, employment, and criminal justice.

Key facts. Cited by 72 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Dec 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 15; 2023: 19; 2024: 16; 2025: 9; 2026: 4.

72 papers.

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  1. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  2. 2021FairFed: Enabling Group Fairness in Federated Learningcited by 114
  3. 2021DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networkscited by 109
  4. 2024Trustworthiness in Retrieval-Augmented Generation Systems: A Surveycited by 83
  5. 2021Post-processing for Individual Fairnesscited by 61
  6. 2022Fairness-aware Adversarial Perturbation Towards Bias Mitigation for Deployed Deep Modelscited by 47
  7. 2022Fairness Reprogrammingcited by 33
  8. 2023Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalizationcited by 31
  9. 2022Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refittingcited by 26
  10. 2023Privacy and Fairness in Federated Learning: on the Perspective of Trade-offcited by 26
  11. 2021Deep Clustering based Fair Outlier Detectioncited by 19
  12. 2024FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classificationcited by 19
38 more
  1. 2022D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Biascited by 18
  2. 2022Minimax AUC Fairness: Efficient Algorithm with Provable Convergencecited by 16
  3. 2022Fairness Score and Process Standardization: Framework for Fairness Certification in Artificial Intelligence Systemscited by 14
  4. 2022Improving Fairness in Image Classification via Sketchingcited by 11
  5. 2022To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontiercited by 10
  6. 2023Mitigating Group Bias in Federated Learning: Beyond Local Fairnesscited by 10
  7. 2021BeFair: Addressing Fairness in the Banking Sectorcited by 8
  8. 2023Disentangling and Operationalizing AI Fairness at LinkedIncited by 7
  9. 2021End-To-End Bias Mitigation: Removing Gender Bias in Deep Learningcited by 6
  10. 2021Social Norm Bias: Residual Harms of Fairness-Aware Algorithmscited by 6
  11. 2023Fairness-aware Vision Transformer via Debiased Self-Attentioncited by 6
  12. 2024A Large-Scale Empirical Study on Improving the Fairness of Image Classification Modelscited by 6
  13. 2024On the (In)Compatibility between Group Fairness and Individual Fairnesscited by 6
  14. 2024FairEHR-CLP: Towards Fairness-Aware Clinical Predictions with Contrastive Learning in Multimodal Electronic Health Recordscited by 6
  15. 2023Mitigating Group Bias in Federated Learning for Heterogeneous Devicescited by 5
  16. 2024GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learningcited by 5
  17. 2022Fair Wrapping for Black-box Predictionscited by 4
  18. 2022FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networkscited by 4
  19. 2023Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairnesscited by 4
  20. 2023Fairness and Bias in Truth Discovery Algorithms: An Experimental Analysiscited by 4
  21. 2023Group-blind optimal transport to group parity and its constrained variantscited by 4
  22. 2023FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scalingcited by 4
  23. 2024A Catalog of Fairness-Aware Practices in Machine Learning Engineeringcited by 4
  24. 2025Unsupervised Search for Ethnic Minorities' Medical Segmentation Training Setcited by 4
  25. 2021Priority-based Post-Processing Bias Mitigation for Individual and Group Fairnesscited by 3
  26. 2024Post-processing fairness with minimal changescited by 3
  27. 2022How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategiescited by 2
  28. 2023Toward Fair Facial Expression Recognition with Improved Distribution Alignmentcited by 2
  29. 2023Mitigating Label Bias in Machine Learning: Fairness through Confident Learningcited by 2
  30. 2024GRAPHGINI: Fostering Individual and Group Fairness in Graph Neural Networkscited by 2
  31. 2024FairFlow: An Automated Approach to Model-based Counterfactual Data Augmentation For NLPcited by 2
  32. 2024Multi-Output Distributional Fairness via Post-Processingcited by 2
  33. 2021Evaluation of Human and Machine Face Detection using a Novel Distinctive Human Appearance Datasetcited by 1
  34. 2023Bias Mitigation Methods for Binary Classification Decision-Making Systems: Survey and Recommendationscited by 1
  35. 2023Towards Fair and Explainable AI using a Human-Centered AI Approachcited by 1
  36. 2023Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directionscited by 1
  37. 2023Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Frameworkcited by 1
  38. 2023Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogatescited by 1

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