| On the sample complexity of the linear quadratic regulator S Dean, H Mania, N Matni, B Recht, S Tu Foundations of Computational Mathematics, 1-47, 2019 | 623 | 2019 |
| Delayed impact of fair machine learning LT Liu, S Dean, E Rolf, M Simchowitz, M Hardt International Conference on Machine Learning, 3150-3158, 2018 | 547 | 2018 |
| Regret bounds for robust adaptive control of the linear quadratic regulator S Dean, H Mania, N Matni, B Recht, S Tu Advances in Neural Information Processing Systems, 4188-4197, 2018 | 304 | 2018 |
| Safely learning to control the constrained linear quadratic regulator S Dean, S Tu, N Matni, B Recht 2019 American Control Conference (ACC), 5582-5588, 2019 | 161 | 2019 |
| Robust guarantees for perception-based control S Dean, N Matni, B Recht, V Ye Learning for Dynamics and Control, 350-360, 2020 | 96 | 2020 |
| Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions S Dean, AJ Taylor, RK Cosner, B Recht, AD Ames arXiv preprint arXiv:2010.16001, 2020 | 88 | 2020 |
| A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics R Dobbe, S Dean, T Gilbert, N Kohli arXiv preprint arXiv:1807.00553, 2018 | 62 | 2018 |
| Recommendations and user agency: the reachability of collaboratively-filtered information S Dean, S Rich, B Recht Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020 | 57 | 2020 |
| Towards robust data-driven control synthesis for nonlinear systems with actuation uncertainty AJ Taylor, VD Dorobantu, S Dean, B Recht, Y Yue, AD Ames 2021 60th IEEE Conference on Decision and Control (CDC), 6469-6476, 2021 | 43 | 2021 |
| Do Offline Metrics Predict Online Performance in Recommender Systems? K Krauth, S Dean, A Zhao, W Guo, M Curmei, B Recht, MI Jordan arXiv preprint arXiv:2011.07931, 2020 | 43 | 2020 |
| Reward reports for reinforcement learning TK Gilbert, N Lambert, S Dean, T Zick, A Snoswell, S Mehta Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 84-130, 2023 | 36 | 2023 |
| Preference dynamics under personalized recommendations S Dean, J Morgenstern Proceedings of the 23rd ACM Conference on Economics and Computation, 795-816, 2022 | 34 | 2022 |
| Certainty equivalent perception-based control S Dean, B Recht Learning for Dynamics and Control, 399-411, 2021 | 34 | 2021 |
| Modeling Content Creator Incentives on Algorithm-Curated Platforms J Hron, K Krauth, MI Jordan, N Kilbertus, S Dean arXiv preprint arXiv:2206.13102, 2022 | 33 | 2022 |
| Balancing competing objectives with noisy data: Score-based classifiers for welfare-aware machine learning E Rolf, M Simchowitz, S Dean, LT Liu, D Bjorkegren, M Hardt, ... International Conference on Machine Learning, 8158-8168, 2020 | 29 | 2020 |
| Axes for Sociotechnical Inquiry in AI Research S Dean, TK Gilbert, N Lambert, T Zick IEEE Transactions on Technology and Society 2 (2), 62-70, 2021 | 15 | 2021 |
| Emergent specialization from participation dynamics and multi-learner retraining S Dean, M Curmei, LJ Ratliff, J Morgenstern, M Fazel arXiv preprint arXiv:2206.02667, 2022 | 13* | 2022 |
| Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems TK Gilbert, S Dean, T Zick, N Lambert arXiv preprint arXiv:2202.05716, 2022 | 9 | 2022 |
| Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability M Curmei, S Dean, B Recht International Conference on Machine Learning, 2265-2275, 2021 | 8 | 2021 |
| AI development for the public interest: From abstraction traps to sociotechnical risks MK Andrus, S Dean, TK Gilbert, N Lambert, T Zick 2020 IEEE International Symposium on Technology and Society (ISTAS), 72-79, 2020 | 8 | 2020 |
