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Fast Fair Regression via Efficient Approximations of Mutual Information

Fast Fair Regression via Efficient Approximations of Mutual Information

14 February 2020
D. Steinberg
Alistair Reid
S. O'Callaghan
Finnian Lattimore
L. McCalman
Tibério S. Caetano
    FaML
ArXiv (abs)PDFHTML

Papers citing "Fast Fair Regression via Efficient Approximations of Mutual Information"

12 / 12 papers shown
Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
Zhecheng Sheng
Jiawei Zhang
Enmao Diao
FaML
323
0
0
01 Nov 2025
Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation
Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation
Ho Ming Lee
Katrien Antonio
Benjamin Avanzi
Lorenzo Marchi
Rui Zhou
FaML
421
2
0
09 Sep 2025
Counterfactually Fair Regression with Double Machine Learning
Counterfactually Fair Regression with Double Machine Learning
Patrick Rehill
FaML
147
1
0
21 Mar 2023
Mean Parity Fair Regression in RKHS
Mean Parity Fair Regression in RKHSInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Shaokui Wei
Jiayin Liu
Bing Li
H. Zha
223
4
0
21 Feb 2023
Practical Approaches for Fair Learning with Multitype and Multivariate
  Sensitive Attributes
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes
Tennison Liu
Alex J. Chan
B. V. Breugel
M. Schaar
FaML
260
5
0
11 Nov 2022
Fair Regression under Sample Selection Bias
Fair Regression under Sample Selection Bias
Wei Du
Xintao Wu
Hanghang Tong
199
5
0
08 Oct 2021
Gradual (In)Compatibility of Fairness Criteria
Gradual (In)Compatibility of Fairness CriteriaAAAI Conference on Artificial Intelligence (AAAI), 2021
Corinna Hertweck
T. Raz
289
15
0
09 Sep 2021
Achieving Fairness with a Simple Ridge Penalty
Achieving Fairness with a Simple Ridge PenaltyStatistics and computing (Stat Comput), 2021
M. Scutari
F. Panero
M. Proissl
FaML
457
17
0
18 May 2021
A Stochastic Optimization Framework for Fair Risk Minimization
A Stochastic Optimization Framework for Fair Risk Minimization
Andrew Lowy
Sina Baharlouei
Rakesh Pavan
Meisam Razaviyayn
Ahmad Beirami
FaML
427
29
0
24 Feb 2021
Learning Invariant Representations and Risks for Semi-supervised Domain
  Adaptation
Learning Invariant Representations and Risks for Semi-supervised Domain AdaptationComputer Vision and Pattern Recognition (CVPR), 2020
Yue Liu
Yezhen Wang
Shanghang Zhang
Dongsheng Li
Trevor Darrell
Kurt Keutzer
Han Zhao
OOD
364
114
0
09 Oct 2020
A minimax framework for quantifying risk-fairness trade-off in
  regression
A minimax framework for quantifying risk-fairness trade-off in regressionAnnals of Statistics (Ann. Stat.), 2020
Evgenii Chzhen
Nicolas Schreuder
FaML
447
42
0
28 Jul 2020
Review of Mathematical frameworks for Fairness in Machine Learning
Review of Mathematical frameworks for Fairness in Machine Learning
E. del Barrio
Paula Gordaliza
Jean-Michel Loubes
FaMLFedML
170
43
0
26 May 2020
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