mlsanityData to 7 Oct 2026

Outside the Echo Chamber: Optimizing the Performative Risk

arXiv 2102.08570 ↗First posted 17 Feb 2021cs.LG stat.MLcited by 95

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Abstract (arXiv)

In performative prediction, predictions guide decision-making and hence can influence the distribution of future data. To date, work on performative prediction has focused on finding performatively stable models, which are the fixed points of repeated retraining. However, stable solutions can be far from optimal when evaluated in terms of the performative risk, the loss experienced by the decision maker when deploying a model. In this paper, we shift attention beyond performative stability and focus on optimizing the performative risk directly. We identify a natural set of properties of the loss function and model-induced distribution shift under which the performative risk is convex, a property which does not follow from convexity of the loss alone. Furthermore, we develop algorithms that leverage our structural assumptions to optimize the performative risk with better sample efficiency than generic methods for derivative-free convex optimization.

Key facts. Cited by 95 papers in the map (data through 7 Oct 2026). Builds on 20 of its 52 references that are in the map. First posted on arXiv 17 Feb 2021.

Builds on

20 of 52 references.

References · 20

  1. 2020Performative Predictioncited by 318
  2. 2015Strategic Classificationcited by 256
  3. 2017Strategic Classification from Revealed Preferencescited by 126
  4. 2019Model-Based Reinforcement Learning with a Generative Model is Minimax Optimalcited by 124
  5. 2020Naive Exploration is Optimal for Online LQRcited by 111
  6. 2018The Social Cost of Strategic Classificationcited by 105
  7. 2019Strategic Classification is Causal Modeling in Disguisecited by 92
  8. 2020Stochastic Optimization for Performative Predictioncited by 92
  9. 2020Performative Prediction in a Stateful Worldcited by 90
  10. 2017Double/Debiased/Neyman Machine Learning of Treatment Effectscited by 76
  11. 2018The Disparate Effects of Strategic Manipulationcited by 75
  12. 2020Causal Strategic Linear Regressioncited by 65
8 more
  1. 2020Stochastic optimization with decision-dependent distributionscited by 65
  2. 2020Maximizing Welfare with Incentive-Aware Evaluation Mechanismscited by 46
  3. 2020Decisions, Counterfactual Explanations and Strategic Behaviorcited by 44
  4. 2017Orthogonal Machine Learning: Power and Limitationscited by 28
  5. 2019A Tutorial on Concentration Bounds for System Identificationcited by 19
  6. 2020From Predictions to Decisions: Using Lookahead Regularizationcited by 19
  7. 2019Experimenting in Equilibriumcited by 16
  8. 2020Gaming Helps! Learning from Strategic Interactions in Natural Dynamicscited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 18; 2023: 10; 2024: 22; 2025: 21; 2026: 15.

95 papers.

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  1. 2022Data Feedback Loops: Model-driven Amplification of Dataset Biasescited by 59
  2. 2021Strategic Classification Made Practicalcited by 58
  3. 2021Who Leads and Who Follows in Strategic Classification?cited by 53
  4. 2023Performative Prediction: Past and Futurecited by 52
  5. 2021Alternative Microfoundations for Strategic Classificationcited by 47
  6. 2022Multiplayer Performative Prediction: Learning in Decision-Dependent Gamescited by 42
  7. 2022Performative Powercited by 42
  8. 2022Regret Minimization with Performative Feedbackcited by 40
  9. 2022Anticipating Performativity by Predicting from Predictionscited by 37
  10. 2022Multi-agent Performative Prediction: From Global Stability and Optimality to Chaoscited by 33
  11. 2023Performative Prediction with Neural Networkscited by 33
  12. 2021Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responsescited by 32
38 more
  1. 2022Making Decisions under Outcome Performativitycited by 32
  2. 2022Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environmentscited by 31
  3. 2023Causal Strategic Classification: A Tale of Two Shiftscited by 30
  4. 2021How to Learn when Data Gradually Reacts to Your Modelcited by 29
  5. 2022Performative Reinforcement Learningcited by 25
  6. 2023Plug-in Performative Optimizationcited by 20
  7. 2021Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimizationcited by 18
  8. 2022Strategic Classification with Graph Neural Networkscited by 14
  9. 2023Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shiftscited by 14
  10. 2024Performative Reinforcement Learning in Gradually Shifting Environmentscited by 13
  11. 2022Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimalitycited by 12
  12. 2023Performative Recommendation: Diversifying Content via Strategic Incentivescited by 12
  13. 2021Approximate Regions of Attraction in Learning with Decision-Dependent Distributionscited by 11
  14. 2023Performative Prediction with Bandit Feedback: Learning through Reparameterizationcited by 11
  15. 2024Addressing Polarization and Unfairness in Performative Predictioncited by 11
  16. 2025Revisiting the Predictability of Performative, Social Eventscited by 11
  17. 2023Zero-Regret Performative Prediction Under Inequality Constraintscited by 10
  18. 2022Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instrumentscited by 9
  19. 2024Optimal Classification under Performative Distribution Shiftcited by 9
  20. 2022Addressing Strategic Manipulation Disparities in Fair Classificationcited by 8
  21. 2024Performative Reinforcement Learning with Linear Markov Decision Processcited by 8
  22. 2025Performative Validity of Recourse Explanationscited by 8
  23. 2024Performative Prediction on Games and Mechanism Designcited by 7
  24. 2024Distributionally Robust Performative Predictioncited by 7
  25. 2022Stochastic Saddle Point Problems with Decision-Dependent Distributionscited by 6
  26. 2022Online Convex Optimization with Unbounded Memorycited by 6
  27. 2024Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Marketscited by 6
  28. 2025A Statistical Case Against Empirical Human-AI Alignmentcited by 6
  29. 2025On Corruption-Robustness in Performative Reinforcement Learningcited by 6
  30. 2022Emergent specialization from participation dynamics and multi-learner retrainingcited by 5
  31. 2023Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flowscited by 5
  32. 2024Learning the Distribution Map in Reverse Causal Performative Predictioncited by 5
  33. 2025Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamicscited by 5
  34. 2025Generalization Bounds and Stopping Rules for Learning with Self-Selected Datacited by 5
  35. 2022Optimizing the Performative Risk under Weak Convexity Assumptionscited by 4
  36. 2024Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Clipping Bias and Remediescited by 4
  37. 2024Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challengescited by 4
  38. 2024The Limitations of Model Retraining in the Face of Performativitycited by 4

50 most cited of 95 All 95 (JSON)