Learning optimal fair decision trees: Trade-offs between interpretability, fairness, and accuracy N Jo, S Aghaei, J Benson, A Gomez, P Vayanos Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 181-192, 2023 | 35* | 2023 |
Learning optimal prescriptive trees from observational data N Jo, S Aghaei, A Gómez, P Vayanos arXiv preprint arXiv:2108.13628, 2021 | 18 | 2021 |
Fairness in contextual resource allocation systems: Metrics and incompatibility results N Jo, B Tang, K Dullerud, S Aghaei, E Rice, P Vayanos Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 11837 …, 2023 | 8 | 2023 |
ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription P Vossler, S Aghaei, N Justin, N Jo, A Gómez, P Vayanos arXiv preprint arXiv:2307.15691, 2023 | 3 | 2023 |
Estimating and implementing conventional fairness metrics with probabilistic protected features H Elzayn, E Black, P Vossler, N Jo, J Goldin, DE Ho 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 161-193, 2024 | 2 | 2024 |
Not (Officially) in My Backyard: Characterizing Informal Accessory Dwelling Units and Informing Housing Policy with Remote Sensing N Jo, A Vallebueno, D Ouyang, DE Ho Journal of the American Planning Association 91 (1), 30-45, 2025 | | 2025 |
Drop a Line, Submit on Time? Randomized Tailored Reminders Improve Pollution Reporting Timeliness E Benami, N Jo, B Ragnauth, DE Ho Randomized Tailored Reminders Improve Pollution Reporting Timeliness …, 2023 | | 2023 |
2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)| 979-8-3503-4950-4/24/$31.00© 2024 IEEE| DOI: 10.1109/SaTML59370. 2024.00043 U Aïvodji, G Anderson, R Anderson, S Aydore, A Azize, D Basu, ... | | |