| Inverse reward design D Hadfield-Menell, S Milli, P Abbeel, S Russell, A Dragan NeurIPS 2016, 2016 | 333 | 2016 |
| The Social Cost of Strategic Classification S Milli, J Miller, AD Dragan, M Hardt FAT* 2019, 2019 | 139 | 2019 |
| Model Reconstruction from Model Explanations S Milli, L Schmidt, AD Dragan, M Hardt FAT* 2019, 2019 | 128 | 2019 |
| Reward-rational (implicit) choice: A unifying formalism for reward learning HJ Jeon, S Milli, AD Dragan NeurIPS 2020, 2020 | 102 | 2020 |
| Strategic classification is causal modeling in disguise J Miller, S Milli, M Hardt International Conference on Machine Learning, 6917-6926, 2020 | 77 | 2020 |
| Should robots be obedient? S Milli, D Hadfield-Menell, A Dragan, S Russell IJCAI 2017, 2017 | 61 | 2017 |
| A rational reinterpretation of dual-process theories S Milli, F Lieder, TL Griffiths Cognition, 2021 | 48 | 2021 |
| When does bounded-optimal metareasoning favor few cognitive systems? S Milli, F Lieder, TL Griffiths AAAI 2017, 4422-4428, 2017 | 45 | 2017 |
| Beyond canonical texts: A computational analysis of fanfiction S Milli, D Bamman Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 40 | 2016 |
| Value-laden Disciplinary Shifts in Machine Learning R Dotan, S Milli FAT* 2020, 2020 | 35 | 2020 |
| From Optimizing Engagement to Measuring Value S Milli, L Belli, M Hardt FaccT, 2021 | 24 | 2021 |
| Interpretable and pedagogical examples S Milli, P Abbeel, I Mordatch arXiv preprint arXiv:1711.00694, 2017 | 19 | 2017 |
| Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning S Milli, AD Dragan UAI 2019, 2019 | 16 | 2019 |
| Strategic adaptation to classifiers: A causal perspective J Miller, S Milli, M Hardt ICML 2020, 2019 | 9 | 2019 |
| Augmenting course material with open access textbooks S Milli, MA Hearst Proceedings of the 11th Workshop on Innovative Use of NLP for Building …, 2016 | 3 | 2016 |
| Causal Inference Struggles with Agency on Online Platforms S Milli, L Belli, M Hardt 2022 ACM Conference on Fairness, Accountability, and Transparency, 357-365, 2022 | 1 | 2022 |
| Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems S Milli, E Pierson, N Garg arXiv preprint arXiv:2305.17428, 2023 | | 2023 |
| Twitter's Algorithm: Amplifying Anger, Animosity, and Affective Polarization S Milli, M Carroll, S Pandey, Y Wang, AD Dragan arXiv preprint arXiv:2305.16941, 2023 | | 2023 |
| Value-aligned recommendations L Belli, S Milli US Patent App. 16/989,870, 2022 | | 2022 |
| Learning Objective Functions from Many Diverse Signals SL Milli University of California, Berkeley, 2022 | | 2022 |
