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Ensuring Fairness Beyond the Training Data

Ensuring Fairness Beyond the Training Data

12 July 2020
Debmalya Mandal
Samuel Deng
Suman Jana
Jeannette M. Wing
Daniel J. Hsu
    FaML
    OOD
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Papers citing "Ensuring Fairness Beyond the Training Data"

9 / 9 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
Towards Fair and Calibrated Models
Towards Fair and Calibrated Models
Anand Brahmbhatt
Vipul Rathore
Mausam
Parag Singla
FaML
19
2
0
16 Oct 2023
Manifestations of Xenophobia in AI Systems
Manifestations of Xenophobia in AI Systems
Nenad Tomašev
J. L. Maynard
Iason Gabriel
24
9
0
15 Dec 2022
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
Sample Selection for Fair and Robust Training
Sample Selection for Fair and Robust Training
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
13
61
0
27 Oct 2021
Certifying Robustness to Programmable Data Bias in Decision Trees
Certifying Robustness to Programmable Data Bias in Decision Trees
Anna P. Meyer
Aws Albarghouthi
Loris Dántoni
27
21
0
08 Oct 2021
Towards Out-Of-Distribution Generalization: A Survey
Towards Out-Of-Distribution Generalization: A Survey
Jiashuo Liu
Zheyan Shen
Yue He
Xingxuan Zhang
Renzhe Xu
Han Yu
Peng Cui
CML
OOD
52
516
0
31 Aug 2021
Characterizing the risk of fairwashing
Characterizing the risk of fairwashing
Ulrich Aivodji
Hiromi Arai
Sébastien Gambs
Satoshi Hara
20
27
0
14 Jun 2021
Trustworthy AI
Trustworthy AI
Jeannette M. Wing
20
214
0
14 Feb 2020
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