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Robust Fairness under Covariate Shift

Robust Fairness under Covariate Shift

11 October 2020
Ashkan Rezaei
Anqi Liu
Omid Memarrast
Brian D. Ziebart
    TTA
    OOD
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Papers citing "Robust Fairness under Covariate Shift"

13 / 13 papers shown
Title
Graph Fairness Learning under Distribution Shifts
Graph Fairness Learning under Distribution Shifts
Yibo Li
Xiao Wang
Yujie Xing
Shaohua Fan
Ruijia Wang
Yaoqi Liu
Chuan Shi
OOD
36
7
0
30 Jan 2024
Learning Fair Policies for Multi-stage Selection Problems from
  Observational Data
Learning Fair Policies for Multi-stage Selection Problems from Observational Data
Zhuangzhuang Jia
G. A. Hanasusanto
P. Vayanos
Weijun Xie
FaML
23
2
0
20 Dec 2023
Towards Fair and Calibrated Models
Towards Fair and Calibrated Models
Anand Brahmbhatt
Vipul Rathore
Mausam
Parag Singla
FaML
21
2
0
16 Oct 2023
Unraveling the Interconnected Axes of Heterogeneity in Machine Learning
  for Democratic and Inclusive Advancements
Unraveling the Interconnected Axes of Heterogeneity in Machine Learning for Democratic and Inclusive Advancements
Maryam Molamohammadi
Afaf Taik
Nicolas Le Roux
G. Farnadi
29
1
0
11 Jun 2023
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation
  Approach
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach
Zhimeng Jiang
Xiaotian Han
Hongye Jin
Guanchu Wang
Rui Chen
Na Zou
Xia Hu
12
13
0
06 Mar 2023
Improving Fair Training under Correlation Shifts
Improving Fair Training under Correlation Shifts
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
27
17
0
05 Feb 2023
How Robust is Your Fairness? Evaluating and Sustaining Fairness under
  Unseen Distribution Shifts
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Haotao Wang
Junyuan Hong
Jiayu Zhou
Zhangyang Wang
OOD
56
11
0
04 Jul 2022
ABCinML: Anticipatory Bias Correction in Machine Learning Applications
ABCinML: Anticipatory Bias Correction in Machine Learning Applications
Abdulaziz A. Almuzaini
C. Bhatt
David M. Pennock
V. Singh
FaML
27
10
0
14 Jun 2022
Social Bias Meets Data Bias: The Impacts of Labeling and Measurement
  Errors on Fairness Criteria
Social Bias Meets Data Bias: The Impacts of Labeling and Measurement Errors on Fairness Criteria
Yiqiao Liao
Parinaz Naghizadeh Ardabili
6
8
0
31 May 2022
Sample Selection for Fair and Robust Training
Sample Selection for Fair and Robust Training
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
15
61
0
27 Oct 2021
Fairness in Machine Learning
Fairness in Machine Learning
L. Oneto
Silvia Chiappa
FaML
256
488
0
31 Dec 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
323
4,212
0
23 Aug 2019
Learning Adversarially Fair and Transferable Representations
Learning Adversarially Fair and Transferable Representations
David Madras
Elliot Creager
T. Pitassi
R. Zemel
FaML
233
674
0
17 Feb 2018
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