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Fair Data Representation for Machine Learning at the Pareto Frontier
Journal of machine learning research (JMLR), 2022
2 January 2022
Shizhou Xu
Thomas Strohmer
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Papers citing
"Fair Data Representation for Machine Learning at the Pareto Frontier"
5 / 5 papers shown
FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport
Pengxi Liu
Yi Shen
Matthew M. Engelhard
Benjamin A. Goldstein
Michael J. Pencina
Nicoleta J. Economou-Zavlanos
Michael M. Zavlanos
201
0
0
05 Aug 2025
WHOMP: Optimizing Randomized Controlled Trials via Wasserstein Homogeneity
Shizhou Xu
Thomas Strohmer
274
0
0
27 Sep 2024
FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024
Zicun Cong
Baoxu Shi
Shan Li
Jaewon Yang
Qi He
Jian Pei
390
12
0
26 Jan 2024
On the (In)Compatibility between Group Fairness and Individual Fairness
Shizhou Xu
Thomas Strohmer
FaML
218
8
0
13 Jan 2024
Fair Wasserstein Coresets
Zikai Xiong
Niccolò Dalmasso
Sanjay Kariyappa
Freddy Lecue
Daniele Magazzeni
Vamsi K. Potluru
T. Balch
Manuela Veloso
465
5
0
09 Nov 2023
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