Learning optimal and fair decision trees for non-discriminative decision-making S Aghaei, MJ Azizi, P Vayanos Proceedings of the AAAI conference on artificial intelligence 33 (01), 1418-1426, 2019 | 237 | 2019 |
Strong optimal classification trees S Aghaei, A Gómez, P Vayanos Operations Research, 2021 | 79 | 2021 |
Learning optimal classification trees: Strong max-flow formulations S Aghaei, A Gomez, P Vayanos International Conference on The Integration of Constraint Programming …, 2020 | 36 | 2020 |
Learning Optimal Fair Decision Trees: Trade-offs Between Interpretability, Fairness, and Accuracy N Jo, S Aghaei, J Benson, A Gomez, P Vayanos AAAI / ACM conference on ARTIFICIAL INTELLIGENCE. ETHICS, AND SOCIETY, 2023 | 18 | 2023 |
Learning Optimal Fair Classification Trees N Jo, S Aghaei, J Benson, A Gómez, P Vayanos International Conference on The Integration of Constraint Programming …, 2022 | 18 | 2022 |
Learning optimal prescriptive trees from observational data N Jo, S Aghaei, A Gómez, P Vayanos arXiv preprint arXiv:2108.13628, 2021 | 18 | 2021 |
Optimal robust classification trees N Justin, S Aghaei, A Gomez, P Vayanos The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2021 | 16 | 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 |
Learning optimal classification trees: strong max-flow formulations (2020) S Aghaei, A Gomez, P Vayanos DOI: https://doi. org/10.48550/arXiv, 2002 | 5 | 2002 |
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 |
Learning Optimal Classification Trees Robust to Distribution Shifts N Justin, S Aghaei, A Gómez, P Vayanos arXiv preprint arXiv:2310.17772, 2023 | | 2023 |