 On Corruption-Robustness in Performative Reinforcement LearningAAAI Conference on Artificial Intelligence (AAAI), 2025 |
 Independent Learning in Performative Markov Potential GamesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025 |
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 Identifying Predictions That Influence the Future: Detecting Performative Concept Drift in Data StreamsAAAI Conference on Artificial Intelligence (AAAI), 2024 |
 Performative Prediction on Games and Mechanism DesignInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 |
 Performative Prediction: Past and FutureStatistical Science (Statist. Sci.), 2023 |
 Zero-Regret Performative Prediction Under Inequality ConstraintsNeural Information Processing Systems (NeurIPS), 2023 |
 Contextual Dynamic Pricing with Strategic BuyersJournal of the American Statistical Association (JASA), 2023 |
 The Risks of Recourse in Binary ClassificationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 |
 Plug-in Performative OptimizationInternational Conference on Machine Learning (ICML), 2023 |
 Algorithmic Censoring in Dynamic Learning SystemsConference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2023 |
 Performative Federated Learning: A Solution to Model-Dependent and
Heterogeneous Distribution ShiftsAAAI Conference on Artificial Intelligence (AAAI), 2023 |
 Performative Prediction with Bandit Feedback: Learning through
ReparameterizationInternational Conference on Machine Learning (ICML), 2023 |
 Performative Prediction with Neural NetworksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 |
 Performative Recommendation: Diversifying Content via Strategic
IncentivesInternational Conference on Machine Learning (ICML), 2023 |
 Online Convex Optimization with Unbounded MemoryNeural Information Processing Systems (NeurIPS), 2022 |
 Making Decisions under Outcome PerformativityInformation Technology Convergence and Services (ITCS), 2022 |
 Data Feedback Loops: Model-driven Amplification of Dataset BiasesInternational Conference on Machine Learning (ICML), 2022 Rohan Taori Tatsunori B. Hashimoto |
 Stochastic Approximation with Decision-Dependent Distributions:
Asymptotic Normality and OptimalityJournal of machine learning research (JMLR), 2022 |
 Performative Reinforcement LearningInternational Conference on Machine Learning (ICML), 2022 |
 Emergent specialization from participation dynamics and multi-learner
retrainingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 |
 Predictor-corrector algorithms for stochastic optimization under gradual
distribution shiftInternational Conference on Learning Representations (ICLR), 2022 |
 Preference Dynamics Under Personalized RecommendationsACM Conference on Economics and Computation (EC), 2022 |
