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Title
Cited by
Cited by
Year
Training individually fair ML models with sensitive subspace robustness
M Yurochkin, A Bower, Y Sun
International Conference on Learning Representations (ICLR), 2019
1192019
Fair pipelines
A Bower, SN Kitchen, L Niss, MJ Strauss, A Vargas, ...
FAT-ML, 2017
552017
The distribution of gaps between summands in generalized Zeckendorf decompositions
A Bower, R Insoft, S Li, SJ Miller, P Tosteson
Journal of Combinatorial Theory, Series A 135, 130-160, 2015
49*2015
Individually Fair Ranking
A Bower, H Eftekhari, M Yurochkin, Y Sun
International Conference on Learning Representations (ICLR), 2021
292021
De-biasing “bias” measurement
K Lum, Y Zhang, A Bower
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
232022
Debiasing representations by removing unwanted variation due to protected attributes
A Bower, L Niss, Y Sun, A Vargo
FAT-ML, 2018
182018
Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics
T Lazovich, L Belli, A Gonzales, A Bower, U Tantipongpipat, K Lum, ...
Patterns 3 (8), 2022
162022
Preference Modeling with Context-Dependent Salient Features
A Bower, L Balzano
International Conference on Machine Learning (ICML), 2020
142020
Random Isn't Always Fair: Candidate Set Imbalance and Exposure Inequality in Recommender Systems
A Bower, K Lum, T Lazovich, K Yee, L Belli
arXiv preprint arXiv:2209.05000, 2022
42022
The landscape of non-convex quadratic feasibility
A Bower, L Jain, L Balzano
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
32018
Coordinate Sum and Difference Sets of d-Dimensional Modular Hyperbolas.
A Bower, R Evans, V Luo, SJ Miller
Integers 13, A31, 2013
32013
Category Theory and Galois Theory
A Bower
Rose-Hulman Undergraduate Mathematics Journal 14 (1), 10, 2013
12013
Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics
T Lazovich, L Belli, A Gonzales, A Bower, U Tantipongpipat, K Lum, ...
Patterns 4 (8), 2023
2023
Training individually fair machine learning algorithms via distributionally robust optimization
S Upadhyay, M Yurochkin, D Mukherjee, Y Sun, ARG Bower, SH Eftekhari, ...
US Patent App. 17/213,167, 2022
2022
Dealing with Intransitivity, Non-Convexity, and Algorithmic Bias in Preference Learning
AR Bower
University of Michigan, 2020
2020
THE FUNDAMENTAL GROUP AND BROUWER’S FIXED POINT THEOREM
A BOWER
2012
Three roads back: whats fair got to do with it?
A Bower
Time 165 (12), 38-39, 2005
2005
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