| A confidence-based approach for balancing fairness and accuracy B Fish, J Kun, ÁD Lelkes Proceedings of the 2016 SIAM international conference on data mining, 144-152, 2016 | 214 | 2016 |
| Gaps in Information Access in Social Networks B Fish, A Bashardoust, D Boyd, S Friedler, C Scheidegger, ... The World Wide Web Conference, 480-490, 2019 | 49* | 2019 |
| Feature selection based on mutual information for human activity recognition B Fish, A Khan, NH Chehade, C Chien, G Pottie 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 39 | 2012 |
| On the computational complexity of mapreduce B Fish, J Kun, AD Lelkes, L Reyzin, G Turán Distributed Computing: 29th International Symposium, DISC 2015, Tokyo, Japan …, 2015 | 29 | 2015 |
| Fair boosting: a case study B Fish, J Kun, AD Lelkes Workshop on Fairness, Accountability, and Transparency in Machine Learning, 2015 | 27 | 2015 |
| When not to design, build, or deploy S Barocas, AJ Biega, B Fish, J Niklas, L Stark Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020 | 26 | 2020 |
| Reflexive design for fairness and other human values in formal models B Fish, L Stark Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 89-99, 2021 | 16 | 2021 |
| On the complexity of learning from label proportions B Fish, L Reyzin arXiv preprint arXiv:2004.03515, 2020 | 15 | 2020 |
| Handling oversampling in dynamic networks using link prediction B Fish, RS Caceres Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015 | 13 | 2015 |
| A supervised approach to time scale detection in dynamic networks B Fish, RS Caceres arXiv preprint arXiv:1702.07752, 2017 | 12* | 2017 |
| Recovering Social Networks by Observing Votes B Fish, Y Huang, L Reyzin | 11 | 2016 |
| The effects of competition and regulation on error inequality in data-driven markets H Elzayn, B Fish Proceedings of the 2020 conference on fairness, accountability, and …, 2020 | 8 | 2020 |
| A task-driven approach to time scale detection in dynamic networks B Fish, RS Caceres Proceedings of the 13th international workshop on mining and learning with …, 2017 | 8 | 2017 |
| Diamond-free subsets in the linear lattices G Sarkis, S Shahriari, PCURC PCURC@ sakai. claremont. edu Order 31, 421-433, 2014 | 8 | 2014 |
| Zero-sum flows of the linear lattice G Sarkis, S Shahriari Finite Fields and Their Applications 31, 108-120, 2015 | 7 | 2015 |
| Sampling Without Compromising Accuracy in Adaptive Data Analysis B Fish, L Reyzin, BIP Rubinstein Algorithmic Learning Theory, 297-318, 2020 | 6* | 2020 |
| Open problem: Meeting times for learning random automata B Fish, L Reyzin Conference on Learning Theory, 8-11, 2017 | 3 | 2017 |
| CSPs and Connectedness: P/NP-Complete Dichotomy for Idempotent, Right Quasigroups RW McGrail, J Belk, S Garber, J Wood, B Fish | 3* | |
| On graph neural network fairness in the presence of heterophilous neighborhoods D Loveland, J Zhu, M Heimann, B Fish, MT Schaub, D Koutra arXiv preprint arXiv:2207.04376, 2022 | 2 | 2022 |
| Responsible computing during covid-19 and beyond S Barocas, AJ Biega, M Boyarskaya, K Crawford, HD Iii, M Dudík, B Fish, ... Communications of the ACM 64 (7), 30-32, 2021 | 2 | 2021 |
Jeremy KunGoogle, Inc.Verified email at google.com
