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Benjamin Fish
Benjamin Fish
Assistant Professor, University of Michigan
Verifierad e-postadress på umich.edu - Startsida
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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
2812016
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
692019
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
402020
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
382012
Fair boosting: a case study
B Fish, J Kun, AD Lelkes
Workshop on Fairness, Accountability, and Transparency in Machine Learning, 5, 2015
352015
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
322015
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
272021
On the complexity of learning from label proportions
B Fish, L Reyzin
arXiv preprint arXiv:2004.03515, 2020
192020
A supervised approach to time scale detection in dynamic networks
B Fish, RS Caceres
arXiv preprint arXiv:1702.07752, 2017
15*2017
Handling oversampling in dynamic networks using link prediction
B Fish, RS Caceres
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015
132015
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
112020
Recovering Social Networks by Observing Votes
B Fish, Y Huang, L Reyzin
102016
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
92022
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
92017
Diamond-free subsets in the linear lattices
G Sarkis, S Shahriari, PCURC PCURC@ sakai. claremont. edu
Order 31, 421-433, 2014
92014
On performance discrepancies across local homophily levels in graph neural networks
D Loveland, J Zhu, M Heimann, B Fish, MT Schaub, D Koutra
Learning on Graphs Conference, 6: 1-6: 30, 2024
82024
Sampling without compromising accuracy in adaptive data analysis
B Fish, L Reyzin, BIP Rubinstein
Algorithmic Learning Theory, 297-318, 2020
8*2020
danah boyd, Sorelle A. Friedler, Carlos Scheidegger, and Suresh Venkatasubramanian. Gaps in information access in social networks
B Fish, A Bashardoust
WWW2019, 480-490, 2019
82019
Zero-sum flows of the linear lattice
G Sarkis, S Shahriari
Finite Fields and Their Applications 31, 108-120, 2015
72015
It’s not fairness, and it’s not fair: the failure of distributional equality and the promise of relational equality in complete-information hiring games
B Fish, L Stark
Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms …, 2022
62022
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Artiklar 1–20