Benjamin Fish
Benjamin Fish
Postdoc, Mila
Verified email at - Homepage
Cited by
Cited by
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
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
On the computational complexity of mapreduce
B Fish, J Kun, AD Lelkes, L Reyzin, G Turán
International symposium on distributed computing, 1-15, 2015
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
Fair boosting: a case study
B Fish, J Kun, AD Lelkes
Workshop on Fairness, Accountability, and Transparency in Machine Learning, 2015
On the complexity of learning from label proportions
B Fish, L Reyzin
arXiv preprint arXiv:2004.03515, 2020
Handling oversampling in dynamic networks using link prediction
B Fish, RS Caceres
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
Recovering Social Networks by Observing Votes
B Fish, Y Huang, L Reyzin
Diamond-free subsets in the linear lattices
G Sarkis, S Shahriari
Order 31 (3), 421-433, 2014
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
A supervised approach to time scale detection in dynamic networks
B Fish, RS Caceres
arXiv preprint arXiv:1702.07752, 2017
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
Zero-sum flows of the linear lattice
G Sarkis, S Shahriari
Finite Fields and Their Applications 31, 108-120, 2015
CSPs and Connectedness: P/NP-Complete Dichotomy for Idempotent, Right Quasigroups
RW McGrail, J Belk, S Garber, J Wood, B Fish
Sampling Without Compromising Accuracy in Adaptive Data Analysis
B Fish, L Reyzin, BIP Rubinstein
Algorithmic Learning Theory, 297-318, 2020
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
Open problem: Meeting times for learning random automata
B Fish, L Reyzin
Conference on Learning Theory, 8-11, 2017
Betweenness centrality profiles in trees
B Fish, R Kushwaha, G Turán
Journal of Complex Networks 5 (5), 776-794, 2017
The Cophylogeny Reconstruction Problem
B Fish
Pomona College, 2013
On the Complexity of Learning a Class Ratio from Unlabeled Data
B Fish, L Reyzin
Journal of Artificial Intelligence Research 69, 1333–1349-1333–1349, 2020
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