{"total":20,"rows":[{"id":"2102.07698","title":"How to Learn when Data Reacts to Your Model: Performative Gradient Descent","created":"2021-02-15","cited_by_count":71,"area":null},{"id":"2103.01028","title":"Information Discrepancy in Strategic Learning","created":"2021-03-01","cited_by_count":48,"area":null},{"id":"2106.12705","title":"Alternative Microfoundations for Strategic Classification","created":"2021-06-24","cited_by_count":47,"area":null},{"id":"2203.06768","title":"Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse","created":"2022-03-13","cited_by_count":40,"area":null},{"id":"2208.07331","title":"Anticipating Performativity by Predicting from Predictions","created":"2022-08-15","cited_by_count":37,"area":null},{"id":"2402.08758","title":"Bayesian Strategic Classification","created":"2024-02-13","cited_by_count":13,"area":null},{"id":"2404.12366","title":"Accounting for AI and Users Shaping One Another: The Role of Mathematical Models","created":"2024-04-18","cited_by_count":11,"area":null},{"id":"2307.05862","title":"Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes","created":"2023-07-12","cited_by_count":10,"area":null},{"id":"2112.02746","title":"Unfairness Despite Awareness: Group-Fair Classification with Strategic Agents","created":"2021-12-06","cited_by_count":9,"area":null},{"id":"2301.13397","title":"Sequential Strategic Screening","created":"2023-01-31","cited_by_count":8,"area":null},{"id":"2412.02000","title":"Who's Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation","created":"2024-12-02","cited_by_count":5,"area":null},{"id":"2505.05211","title":"Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality","created":"2025-05-08","cited_by_count":5,"area":null},{"id":"2412.01344","title":"Practical Performative Policy Learning with Strategic Agents","created":"2024-12-02","cited_by_count":3,"area":null},{"id":"2204.01884","title":"Policy Learning with Competing Agents","created":"2022-04-04","cited_by_count":2,"area":null},{"id":"2301.12884","title":"Incentives to Offer Algorithmic Recourse","created":"2023-01-27","cited_by_count":2,"area":null},{"id":"2410.02273","title":"Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse","created":"2024-10-03","cited_by_count":2,"area":null},{"id":"2502.11981","title":"Welfare as a Guiding Principle for Machine Learning -- From Compass, to Lens, to Roadmap","created":"2025-02-17","cited_by_count":2,"area":null},{"id":"2206.11400","title":"Program Targeting with Machine Learning and Mobile Phone Data: Evidence from an Anti-Poverty Intervention in Afghanistan","created":"2022-06-22","cited_by_count":1,"area":null},{"id":"2604.22230","title":"Performance Manipulation: Labor Market Implications in AI-assisted Era","created":"2026-04-24","cited_by_count":1,"area":null},{"id":"2606.30136","title":"Robust Strategic Classification under Decision-Dependent Cost Uncertainty","created":"2026-06-29","cited_by_count":0,"area":null}],"next_cursor":null}