mlsanityData to 14 Oct 2026

Classification Under Strategic Self-Selection

arXiv 2402.15274 ↗First posted 23 Feb 2024cs.LGcited by 7

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Abstract (arXiv)

When users stand to gain from certain predictions, they are prone to act strategically to obtain favorable predictive outcomes. Whereas most works on strategic classification consider user actions that manifest as feature modifications, we study a novel setting in which users decide -- in response to the learned classifier -- whether to at all participate (or not). For learning approaches of increasing strategic awareness, we study the effects of self-selection on learning, and the implications of learning on the composition of the self-selected population. We then propose a differentiable framework for learning under self-selective behavior, which can be optimized effectively. We conclude with experiments on real data and simulated behavior that both complement our analysis and demonstrate the utility of our approach.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 29 of its 40 references that are in the map. First posted on arXiv 23 Feb 2024.

Builds on

29 of 40 references.

References · 29

  1. 2018A Reductions Approach to Fair Classificationcited by 587
  2. 2017On Fairness and Calibrationcited by 406
  3. 2015Strategic Classificationcited by 257
  4. 2021A survey on datasets for fairness-aware machine learningcited by 157
  5. 2021On Calibration and Out-of-domain Generalizationcited by 134
  6. 2019Strategic Classification is Causal Modeling in Disguisecited by 92
  7. 2021Strategic Classification in the Darkcited by 66
  8. 2020Stochastic optimization with decision-dependent distributionscited by 65
  9. 2020PAC-Learning for Strategic Classificationcited by 50
  10. 2021Information Discrepancy in Strategic Learningcited by 48
  11. 2021Alternative Microfoundations for Strategic Classificationcited by 47
  12. 2022Anticipating Performativity by Predicting from Predictionscited by 37
17 more
  1. 2022Generalized Strategic Classification and the Case of Aligned Incentivescited by 34
  2. 2023Strategic Classification under Unknown Personalized Manipulationcited by 24
  3. 2023Plug-in Performative Optimizationcited by 22
  4. 2020Linear Classifiers that Encourage Constructive Adaptationcited by 16
  5. 2021Fair Sequential Selection Using Supervised Learning Modelscited by 16
  6. 2022Improving Screening Processes via Calibrated Subset Selectioncited by 16
  7. 2022Strategic Classification with Graph Neural Networkscited by 14
  8. 2023One-Shot Strategic Classification Under Unknown Costscited by 13
  9. 2022Modeling Attrition in Recommender Systems with Departing Banditscited by 11
  10. 2023Strategic Apple Tastingcited by 10
  11. 2020Classification with Strategically Withheld Datacited by 9
  12. 2022Multi Stage Screening: Enforcing Fairness and Maximizing Efficiency in a Pre-Existing Pipelinecited by 8
  13. 2023Sequential Strategic Screeningcited by 8
  14. 2022What Makes A Good Fisherman? Linear Regression under Self-Selection Biascited by 7
  15. 2023The Gatekeeper Effect: The Implications of Pre-Screening, Self-selection, and Bias for Hiring Processescited by 3
  16. 2023On the Within-Group Fairness of Screening Classifierscited by 2
  17. 2023Screening with Disadvantaged Agentscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 1.

7 papers.

  1. 2024Learning under Imitative Strategic Behavior with Unforeseeable Outcomescited by 8
  2. 2025A Market for Accuracy: Classification under Competitioncited by 6
  3. 2025Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causalitycited by 5
  4. 2025Welfare as a Guiding Principle for Machine Learning -- From Compass, to Lens, to Roadmapcited by 2
  5. 2026Multi-Level Strategic Classification: Incentivizing Improvement through Promotion and Relegation Dynamicscited by 1
  6. 2024Adjusting Pretrained Backbones for Performativitycited by 0
  7. 2025Evolutionary Prediction Gamescited by 0