Fa* ir: A fair top-k ranking algorithm M Zehlike, F Bonchi, C Castillo, S Hajian, M Megahed, R Baeza-Yates Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 518 | 2017 |
Reducing disparate exposure in ranking: A learning to rank approach M Zehlike, C Castillo Proceedings of the web conference 2020, 2849-2855, 2020 | 181 | 2020 |
Two-sided fairness for repeated matchings in two-sided markets: A case study of a ride-hailing platform T Sühr, AJ Biega, M Zehlike, KP Gummadi, A Chakraborty Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 149 | 2019 |
Fairness in ranking: A survey M Zehlike, K Yang, J Stoyanovich arXiv preprint arXiv:2103.14000, 2021 | 98 | 2021 |
Fairness in ranking, part i: Score-based ranking M Zehlike, K Yang, J Stoyanovich ACM Computing Surveys 55 (6), 1-36, 2022 | 76 | 2022 |
Fairness in ranking, part ii: Learning-to-rank and recommender systems M Zehlike, K Yang, J Stoyanovich ACM Computing Surveys 55 (6), 1-41, 2022 | 61 | 2022 |
Matching code and law: achieving algorithmic fairness with optimal transport M Zehlike, P Hacker, E Wiedemann Data Mining and Knowledge Discovery 34 (1), 163-200, 2020 | 60 | 2020 |
Fair ranking: a critical review, challenges, and future directions GK Patro, L Porcaro, L Mitchell, Q Zhang, M Zehlike, N Garg Proceedings of the 5th ACM Conference on Fairness, Accountability, and …, 2022 | 55 | 2022 |
Fair Top-k Ranking with multiple protected groups M Zehlike, T Sühr, R Baeza-Yates, F Bonchi, C Castillo, S Hajian Information processing & management 59 (1), 102707, 2022 | 54 | 2022 |
Fairsearch: A tool for fairness in ranked search results M Zehlike, T Sühr, C Castillo, I Kitanovski Companion proceedings of the web conference 2020, 172-175, 2020 | 29 | 2020 |
Fairness measures: datasets and software for detecting algorithmic discrimination M Zehlike, C Castillo, F Bonchi, S Hajian, M Megahed URL http://fairness-measures. org, 2017 | 13* | 2017 |
Beyond Incompatibility: Trade-offs between Mutually Exclusive Fairness Criteria in Machine Learning and Law M Zehlike, A Loosley, H Jonsson, E Wiedemann, P Hacker https://arxiv.org/abs/2212.00469, 2022 | 5* | 2022 |
Tutorials at the web conference 2023 V Fionda, O Hartig, R Abdolazimi, S Amer-Yahia, H Chen, X Chen, P Cui, ... Companion Proceedings of the ACM Web Conference 2023, 648-658, 2023 | 4 | 2023 |
A note on the significance adjustment for FA* IR with two protected groups M Zehlike, T Sühr, C Castillo arXiv preprint arXiv:2012.12795, 2020 | 2 | 2020 |
Towards a Flexible Framework for Algorithmic Fairness P Hacker, E Wiedemann, M Zehlike arXiv preprint arXiv:2010.07848, 2020 | 2 | 2020 |
Fairness in Rankings M Zehlike Humboldt-Universität zu Berlin, 2022 | 1 | 2022 |
Fairness in Ranking: From Values to Technical Choices and Back J Stoyanovich, M Zehlike, K Yang Companion of the 2023 International Conference on Management of Data, 7-12, 2023 | | 2023 |
AI in Higher Education: Ethical Concerns for Students with Disabilities O Pierrès, A Darvishy, M Christen, JM Alvarez, A Fabris, C Heitz, ... CEUR Workshop Proceedings, 7-9, 2023 | | 2023 |
FS: A Tool For Fairness in Ranked Search Results M Zehlike, T Sühr, C Castillo, I Kitanovski | | 2020 |
Body Measurement Prediction Fairness AJ Loosley, A Seifoddini, A Canopoli, M Zehlike | | |