| Datasheets for datasets T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, HD Iii, ... Communications of the ACM 64 (12), 86-92, 2021 | 2493 | 2021 |
| Fairness in learning: Classic and contextual bandits M Joseph, M Kearns, JH Morgenstern, A Roth Advances in neural information processing systems 29, 325-333, 2016 | 546 | 2016 |
| A convex framework for fair regression R Berk, H Heidari, S Jabbari, M Joseph, M Kearns, J Morgenstern, S Neel, ... FAT/ML 2017, 2017 | 397 | 2017 |
| Predictive inequity in object detection B Wilson, J Hoffman, J Morgenstern arXiv preprint arXiv:1902.11097, 2019 | 292 | 2019 |
| Fairness in reinforcement learning S Jabbari, M Joseph, M Kearns, J Morgenstern, A Roth Proceedings of the 34th International Conference on Machine Learning, 1617-1626, 2016 | 249* | 2016 |
| FairVis: Visual analytics for discovering intersectional bias in machine learning ÁA Cabrera, W Epperson, F Hohman, M Kahng, J Morgenstern, DH Chau 2019 IEEE Conference on Visual Analytics Science and Technology (VAST), 46-56, 2019 | 235 | 2019 |
| On the pseudo-dimension of nearly optimal auctions JH Morgenstern, T Roughgarden Advances in Neural Information Processing Systems 28, 136-144, 2015 | 214 | 2015 |
| Fair k-center clustering for data summarization M Kleindessner, P Awasthi, J Morgenstern Proceedings of the 36th International Conference on Machine Learning (ICML …, 2019 | 201 | 2019 |
| Guarantees for spectral clustering with fairness constraints M Kleindessner, S Samadi, P Awasthi, J Morgenstern Proceedings of the 36th International Conference on Machine Learning, 2019 | 194 | 2019 |
| Meritocratic fairness for infinite and contextual bandits M Joseph, M Kearns, J Morgenstern, S Neel, A Roth Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 158-163, 2016 | 192* | 2016 |
| On the compatibility of privacy and fairness R Cummings, V Gupta, D Kimpara, J Morgenstern Adjunct publication of the 27th conference on user modeling, adaptation and …, 2019 | 187 | 2019 |
| The Price of Fair PCA: One Extra Dimension S Samadi, U Tantipongpipat, J Morgenstern, M Singh, S Vempala Conference on Neural Information Processing Systems (NIPS) 2018, 2018 | 178 | 2018 |
| Learning Simple Auctions J Morgenstern, T Roughgarden COLT 2016, 1298-1318, 2016 | 148 | 2016 |
| Diversity and inclusion metrics in subset selection M Mitchell, D Baker, N Moorosi, E Denton, B Hutchinson, A Hanna, ... Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 117-123, 2020 | 118 | 2020 |
| A smoothed analysis of the greedy algorithm for the linear contextual bandit problem S Kannan, JH Morgenstern, A Roth, B Waggoner, ZS Wu Advances in neural information processing systems 31, 2231–2241, 2018 | 112 | 2018 |
| Equalized odds postprocessing under imperfect group information P Awasthi, M Kleindessner, J Morgenstern International conference on artificial intelligence and statistics, 1770-1780, 2020 | 109 | 2020 |
| How bad is selfish voting? S Brânzei, I Caragiannis, J Morgenstern, A Procaccia Proceedings of the AAAI conference on artificial intelligence 27 (1), 138-144, 2013 | 100 | 2013 |
| Impartial Peer Review D Kurokawa, O Lev, J Morgenstern, A Procaccia International Joint Conference on Artificial Intelligence 15, 582-588, 2015 | 84 | 2015 |
| Active sampling for min-max fairness J Abernethy, P Awasthi, M Kleindessner, J Morgenstern, C Russell, ... Proceedings of the 39th International Conference on Machine Learning 162, 53-65, 2020 | 71* | 2020 |
| Evaluating fairness of machine learning models under uncertain and incomplete information P Awasthi, A Beutel, M Kleindessner, J Morgenstern, X Wang Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021 | 64 | 2021 |
Aaron RothProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu