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Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
v1v2 (latest)

Towards Harmless Rawlsian Fairness Regardless of Demographic Prior

4 November 2024
Xuanqian Wang
Jing Li
Ivor Tsang
Yew-Soon Ong
ArXiv (abs)PDFHTMLGithub (2★)

Papers citing "Towards Harmless Rawlsian Fairness Regardless of Demographic Prior"

17 / 17 papers shown
Title
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints
Enforcing Fairness Where It Matters: An Approach Based on Difference-of-Convex Constraints
Yutian He
Yankun Huang
Yao Yao
Qihang Lin
FaML
53
0
0
18 May 2025
Just Train Twice: Improving Group Robustness without Training Group
  Information
Just Train Twice: Improving Group Robustness without Training Group Information
Emmy Liu
Behzad Haghgoo
Annie S. Chen
Aditi Raghunathan
Pang Wei Koh
Shiori Sagawa
Percy Liang
Chelsea Finn
OOD
100
562
0
19 Jul 2021
DORO: Distributional and Outlier Robust Optimization
DORO: Distributional and Outlier Robust Optimization
Runtian Zhai
Chen Dan
J. Zico Kolter
Pradeep Ravikumar
53
62
0
11 Jun 2021
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases
  in Related Features
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features
Tianxiang Zhao
Enyan Dai
Kai Shu
Suhang Wang
FaML
50
57
0
29 Apr 2021
Characterizing Fairness Over the Set of Good Models Under Selective
  Labels
Characterizing Fairness Over the Set of Good Models Under Selective Labels
Amanda Coston
Ashesh Rambachan
Alexandra Chouldechova
FaML
93
85
0
02 Jan 2021
Minimax Pareto Fairness: A Multi Objective Perspective
Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
FaML
77
193
0
03 Nov 2020
Fairness without Demographics through Adversarially Reweighted Learning
Fairness without Demographics through Adversarially Reweighted Learning
Preethi Lahoti
Alex Beutel
Jilin Chen
Kang Lee
Flavien Prost
Nithum Thain
Xuezhi Wang
Ed H. Chi
FaML
121
338
0
23 Jun 2020
Active Sampling for Min-Max Fairness
Active Sampling for Min-Max Fairness
Jacob D. Abernethy
Pranjal Awasthi
Matthäus Kleindessner
Jamie Morgenstern
Chris Russell
Jie Zhang
FaML
46
50
0
11 Jun 2020
Inherent Tradeoffs in Learning Fair Representations
Inherent Tradeoffs in Learning Fair Representations
Han Zhao
Geoffrey J. Gordon
FaML
55
217
0
19 Jun 2019
ProPublica's COMPAS Data Revisited
ProPublica's COMPAS Data Revisited
M. Barenstein
FaML
44
51
0
11 Jun 2019
Learning Models with Uniform Performance via Distributionally Robust
  Optimization
Learning Models with Uniform Performance via Distributionally Robust Optimization
John C. Duchi
Hongseok Namkoong
OOD
66
423
0
20 Oct 2018
Learning to Reweight Examples for Robust Deep Learning
Learning to Reweight Examples for Robust Deep Learning
Mengye Ren
Wenyuan Zeng
Binh Yang
R. Urtasun
OODNoLa
149
1,431
0
24 Mar 2018
Variance-based regularization with convex objectives
Variance-based regularization with convex objectives
John C. Duchi
Hongseok Namkoong
76
351
0
08 Oct 2016
Equality of Opportunity in Supervised Learning
Equality of Opportunity in Supervised Learning
Moritz Hardt
Eric Price
Nathan Srebro
FaML
233
4,330
0
07 Oct 2016
Certifying and removing disparate impact
Certifying and removing disparate impact
Michael Feldman
Sorelle A. Friedler
John Moeller
C. Scheidegger
Suresh Venkatasubramanian
FaML
204
1,993
0
11 Dec 2014
Deep Learning Face Attributes in the Wild
Deep Learning Face Attributes in the Wild
Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
247
8,426
0
28 Nov 2014
Empirical Bernstein Bounds and Sample Variance Penalization
Empirical Bernstein Bounds and Sample Variance Penalization
Andreas Maurer
Massimiliano Pontil
410
545
0
21 Jul 2009
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