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Benjamin Fish
Benjamin Fish
Assistant Professor, University of Michigan
Zweryfikowany adres z umich.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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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
2512016
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
592019
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
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
332020
Fair boosting: a case study
B Fish, J Kun, AD Lelkes
Workshop on Fairness, Accountability, and Transparency in Machine Learning, 5, 2015
312015
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
312015
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
262021
On the complexity of learning from label proportions
B Fish, L Reyzin
arXiv preprint arXiv:2004.03515, 2020
182020
A supervised approach to time scale detection in dynamic networks
B Fish, RS Caceres
arXiv preprint arXiv:1702.07752, 2017
14*2017
Handling oversampling in dynamic networks using link prediction
B Fish, RS Caceres
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015
142015
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
132019
Recovering Social Networks by Observing Votes
B Fish, Y Huang, L Reyzin
102016
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
92020
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
Sampling without compromising accuracy in adaptive data analysis
B Fish, L Reyzin, BIP Rubinstein
Algorithmic Learning Theory, 297-318, 2020
7*2020
Zero-sum flows of the linear lattice
G Sarkis, S Shahriari
Finite Fields and Their Applications 31, 108-120, 2015
72015
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
62022
Open problem: Meeting times for learning random automata
B Fish, L Reyzin
Conference on Learning Theory, 8-11, 2017
32017
CSPs and Connectedness: P/NP-Complete Dichotomy for Idempotent, Right Quasigroups
RW McGrail, J Belk, S Garber, J Wood, B Fish
3*
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