mlsanityData to 7 Oct 2026

Fairness Through Computationally-Bounded Awareness

arXiv 1803.03239 ↗First posted 8 Mar 2018cs.LG cs.CC cs.DScited by 55

Not on the map. Why?

Abstract (arXiv)

We study the problem of fair classification within the versatile framework of Dwork et al. [ITCS '12], which assumes the existence of a metric that measures similarity between pairs of individuals. Unlike earlier work, we do not assume that the entire metric is known to the learning algorithm; instead, the learner can query this arbitrary metric a bounded number of times. We propose a new notion of fairness called metric multifairness and show how to achieve this notion in our setting. Metric multifairness is parameterized by a similarity metric d on pairs of individuals to classify and a rich collection cal C of (possibly overlapping) "comparison sets" over pairs of individuals. At a high level, metric multifairness guarantees that similar subpopulations are treated similarly, as long as these subpopulations are identified within the class cal C.

Key facts. Cited by 55 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Mar 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2020: 1; 2021: 12; 2022: 18; 2023: 6; 2024: 8; 2025: 6; 2026: 4.

55 papers.

Sort:

By area:

  1. 2020Aligning AI With Shared Human Valuescited by 706
  2. 2021Trustworthy AI: From Principles to Practicescited by 206
  3. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 162
  4. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  5. 2021Trustworthy AI: A Computational Perspectivecited by 93
  6. 2022Fairness in Graph Mining: A Surveycited by 76
  7. 2022Practical Adversarial Multivalid Conformal Predictioncited by 65
  8. 2021Online Multivalid Learning: Means, Moments, and Prediction Intervalscited by 48
  9. 2022Low-Degree Multicalibrationcited by 44
  10. 2023A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challengescited by 41
  11. 2021Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communitiescited by 40
  12. 2022Making Decisions under Outcome Performativitycited by 32
38 more
  1. 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
  2. 2021Algorithm Fairness in AI for Medicine and Healthcarecited by 21
  3. 2022A Survey on Fairness for Machine Learning on Graphscited by 20
  4. 2022What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspectivecited by 18
  5. 2021Modeling Techniques for Machine Learning Fairness: A Surveycited by 17
  6. 2022Omnipredictors for Constrained Optimizationcited by 14
  7. 2021Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classificationcited by 13
  8. 2021Individually Fair Gradient Boostingcited by 12
  9. 2021Beyond "Fairness:" Structural (In)justice Lenses on AI for Educationcited by 12
  10. 2022Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothingcited by 11
  11. 2022A Human-Centric Take on Model Monitoringcited by 9
  12. 2022Survey on Fairness Notions and Related Tensionscited by 9
  13. 2023Fair Classifiers that Abstain without Harmcited by 8
  14. 2024What Constitutes a Less Discriminatory Algorithm?cited by 8
  15. 2021Fair Representations by Compressioncited by 7
  16. 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Toolscited by 7
  17. 2024FairEHR-CLP: Towards Fairness-Aware Clinical Predictions with Contrastive Learning in Multimodal Electronic Health Recordscited by 6
  18. 2022Individually Fair Learning with One-Sided Feedbackcited by 5
  19. 2023Fairness in Matching under Uncertaintycited by 5
  20. 2024What is Fair? Defining Fairness in Machine Learning for Healthcited by 5
  21. 2022Fast Feature Selection with Fairness Constraintscited by 4
  22. 2022Manifestations of Xenophobia in AI Systemscited by 4
  23. 2023Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spacescited by 4
  24. 2024Distribution-Specific Auditing For Subgroup Fairnesscited by 4
  25. 2024Diversity-aware clustering: Computational Complexity and Approximation Algorithmscited by 3
  26. 2024Monotone Individual Fairnesscited by 3
  27. 2025A Design Framework for operationalizing Trustworthy Artificial Intelligence in Healthcare: Requirements, Tradeoffs and Challenges for its Clinical Adoptioncited by 3
  28. 2022Metric-Fair Classifier Derandomizationcited by 2
  29. 2024Learning Fairer Representations with FairVICcited by 2
  30. 2024Improving Fairness in Credit Lending Models using Subgroup Threshold Optimizationcited by 1
  31. 2021Non-Comparative Fairness for Human-Auditing and Its Relation to Traditional Fairness Notionscited by 0
  32. 2022Repairing Group-Level Errors for DNNs Using Weighted Regularizationcited by 0
  33. 2022On Disentangled and Locally Fair Representationscited by 0
  34. 2022Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributionscited by 0
  35. 2025General Post-Processing Framework for Fairness Adjustment of Machine Learning Modelscited by 0
  36. 2025The Fair Game: Auditing & Debiasing AI Algorithms Over Timecited by 0
  37. 2025Controllable Pareto Trade-off between Fairness and Accuracycited by 0
  38. 2025Happiness as a Measure of Fairnesscited by 0

50 most cited of 55 All 55 (JSON)