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  4. Cited By
Fairness Under Unawareness: Assessing Disparity When Protected Class Is
  Unobserved

Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved

27 November 2018
Jiahao Chen
Nathan Kallus
Xiaojie Mao
G. Svacha
Madeleine Udell
ArXiv (abs)PDFHTML

Papers citing "Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved"

50 / 63 papers shown
Title
Critical Appraisal of Fairness Metrics in Clinical Predictive AI
Critical Appraisal of Fairness Metrics in Clinical Predictive AI
João Matos
Ben Van Calster
Leo Anthony Celi
Paula Dhiman
J. Gichoya
R. Riley
Chris Russell
Sara Khalid
Gary S. Collins
17
0
0
20 Jun 2025
Testing for Causal Fairness
Testing for Causal Fairness
Jiarun Fu
LiZhong Ding
Pengqi Li
Qiuning Wei
Yurong Cheng
Xu Chen
88
0
0
18 Feb 2025
A Catalog of Fairness-Aware Practices in Machine Learning Engineering
A Catalog of Fairness-Aware Practices in Machine Learning Engineering
Gianmario Voria
Giulia Sellitto
Carmine Ferrara
Francesco Abate
A. Lucia
F. Ferrucci
Gemma Catolino
Fabio Palomba
FaML
111
3
0
29 Aug 2024
Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
Usman Gohar
Zeyu Tang
Jialu Wang
Kun Zhang
Peter Spirtes
Yang Liu
Lu Cheng
FaML
124
4
0
10 Jun 2024
Specification Overfitting in Artificial Intelligence
Specification Overfitting in Artificial Intelligence
Benjamin Roth
Pedro Henrique Luz de Araujo
Yuxi Xia
Saskia Kaltenbrunner
Christoph Korab
233
1
0
13 Mar 2024
Fairness Risks for Group-conditionally Missing Demographics
Fairness Risks for Group-conditionally Missing Demographics
Kaiqi Jiang
Wenzhe Fan
Mao Li
Xinhua Zhang
186
0
0
20 Feb 2024
A Canonical Data Transformation for Achieving Inter- and Within-group
  Fairness
A Canonical Data Transformation for Achieving Inter- and Within-group Fairness
Zachary McBride Lazri
Ivan Brugere
Xin Tian
Dana Dachman-Soled
Antigoni Polychroniadou
Danial Dervovic
Min Wu
53
1
0
23 Oct 2023
Improving Fairness in Adaptive Social Exergames via Shapley Bandits
Improving Fairness in Adaptive Social Exergames via Shapley Bandits
Robert C. Gray
Jennifer Villareale
T. Fox
Diane H Dallal
Santiago Ontañón
D. Arigo
S. Jabbari
Jichen Zhu
55
4
0
18 Feb 2023
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with
  Counterfactual Reasoning
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning
Giandomenico Cornacchia
Vito Walter Anelli
Fedelucio Narducci
Azzurra Ragone
E. Sciascio
FaML
47
0
0
16 Feb 2023
Fairness and Sequential Decision Making: Limits, Lessons, and
  Opportunities
Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities
Samer B. Nashed
Justin Svegliato
Su Lin Blodgett
FaML
58
6
0
13 Jan 2023
Fair Ranking with Noisy Protected Attributes
Fair Ranking with Noisy Protected Attributes
Anay Mehrotra
Nisheeth K. Vishnoi
89
19
0
30 Nov 2022
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With
  Smooth Sensitivity
Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity
Faisal Hamman
Jiahao Chen
Sanghamitra Dutta
66
9
0
03 Nov 2022
Understanding Practices, Challenges, and Opportunities for User-Engaged
  Algorithm Auditing in Industry Practice
Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice
Wesley Hanwen Deng
B. Guo
Alicia DeVrio
Hong Shen
Motahhare Eslami
Kenneth Holstein
MLAU
106
65
0
07 Oct 2022
Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic
  Fairness Research with U.S. Fair Lending Regulation
Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with U.S. Fair Lending Regulation
Indra Elizabeth Kumar
Keegan E. Hines
John P. Dickerson
FaML
84
23
0
05 Oct 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
Max Hort
Zhenpeng Chen
Jie M. Zhang
Mark Harman
Federica Sarro
FaMLAI4CE
107
177
0
14 Jul 2022
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among
  Complexity, Leakage, and Utility
Bottlenecks CLUB: Unifying Information-Theoretic Trade-offs Among Complexity, Leakage, and Utility
Behrooz Razeghi
Flavio du Pin Calmon
Deniz Gunduz
Svyatoslav Voloshynovskiy
58
16
0
11 Jul 2022
Quantifying Feature Contributions to Overall Disparity Using Information
  Theory
Quantifying Feature Contributions to Overall Disparity Using Information Theory
Sanghamitra Dutta
Praveen Venkatesh
P. Grover
FAtt
47
5
0
16 Jun 2022
What's the Harm? Sharp Bounds on the Fraction Negatively Affected by
  Treatment
What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment
Nathan Kallus
78
23
0
20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
He Zhang
Bang Wu
Lizhen Qu
Shirui Pan
Hanghang Tong
Jian Pei
139
110
0
16 May 2022
Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of
  Demographic Data Collection in the Pursuit of Fairness
Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness
Mckane Andrus
Sarah Villeneuve
FaML
103
51
0
18 Apr 2022
Estimating Structural Disparities for Face Models
Estimating Structural Disparities for Face Models
Shervin Ardeshir
Cristina Segalin
Nathan Kallus
CVBM
69
5
0
13 Apr 2022
A Fair Pricing Model via Adversarial Learning
A Fair Pricing Model via Adversarial Learning
Vincent Grari
Arthur Charpentier
Marcin Detyniecki
76
14
0
24 Feb 2022
Explainable Medical Imaging AI Needs Human-Centered Design: Guidelines
  and Evidence from a Systematic Review
Explainable Medical Imaging AI Needs Human-Centered Design: Guidelines and Evidence from a Systematic Review
Haomin Chen
Catalina Gomez
Chien-Ming Huang
Mathias Unberath
114
131
0
21 Dec 2021
Algorithm Fairness in AI for Medicine and Healthcare
Algorithm Fairness in AI for Medicine and Healthcare
Richard J. Chen
Tiffany Y. Chen
Jana Lipkova
Judy J. Wang
Drew F. K. Williamson
Ming Y. Lu
S. Sahai
Faisal Mahmood
FaML
150
47
0
01 Oct 2021
A Sociotechnical View of Algorithmic Fairness
A Sociotechnical View of Algorithmic Fairness
Mateusz Dolata
Stefan Feuerriegel
Gerhard Schwabe
FaML
76
101
0
27 Sep 2021
Fairness without the sensitive attribute via Causal Variational
  Autoencoder
Fairness without the sensitive attribute via Causal Variational Autoencoder
Vincent Grari
Sylvain Lamprier
Marcin Detyniecki
70
30
0
10 Sep 2021
Multiaccurate Proxies for Downstream Fairness
Multiaccurate Proxies for Downstream Fairness
Emily Diana
Wesley Gill
Michael Kearns
K. Kenthapadi
Aaron Roth
Saeed Sharifi-Malvajerdi
80
22
0
09 Jul 2021
Unaware Fairness: Hierarchical Random Forest for Protected Classes
Unaware Fairness: Hierarchical Random Forest for Protected Classes
Xian Li
21
0
0
30 Jun 2021
Fairness via Representation Neutralization
Fairness via Representation Neutralization
Mengnan Du
Subhabrata Mukherjee
Guanchu Wang
Ruixiang Tang
Ahmed Hassan Awadallah
Helen Zhou
90
81
0
23 Jun 2021
Fair Classification with Adversarial Perturbations
Fair Classification with Adversarial Perturbations
L. E. Celis
Anay Mehrotra
Nisheeth K. Vishnoi
FaML
60
32
0
10 Jun 2021
Measuring Model Fairness under Noisy Covariates: A Theoretical
  Perspective
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective
Flavien Prost
Pranjal Awasthi
Nicholas Blumm
A. Kumthekar
Trevor Potter
Li Wei
Xuezhi Wang
Ed H. Chi
Jilin Chen
Alex Beutel
90
16
0
20 May 2021
When Fair Ranking Meets Uncertain Inference
When Fair Ranking Meets Uncertain Inference
Avijit Ghosh
Ritam Dutt
Christo Wilson
109
46
0
05 May 2021
Hard Choices and Hard Limits for Artificial Intelligence
Hard Choices and Hard Limits for Artificial Intelligence
B. Goodman
28
4
0
04 May 2021
Strong Optimal Classification Trees
Strong Optimal Classification Trees
S. Aghaei
Andrés Gómez
P. Vayanos
70
42
0
29 Mar 2021
Responsible AI: Gender bias assessment in emotion recognition
Responsible AI: Gender bias assessment in emotion recognition
Artem Domnich
G. Anbarjafari
149
50
0
21 Mar 2021
RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of
  Opportunity
RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity
David Liu
Zohair Shafi
W. Fleisher
Tina Eliassi-Rad
Scott Alfeld
47
9
0
16 Mar 2021
Evaluating Fairness of Machine Learning Models Under Uncertain and
  Incomplete Information
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information
Pranjal Awasthi
Alex Beutel
Matthaeus Kleindessner
Jamie Morgenstern
Xuezhi Wang
FaML
95
58
0
16 Feb 2021
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning
  Models on MIMIC-IV Dataset
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset
Chuizheng Meng
Loc Trinh
Nan Xu
Yan Liu
67
30
0
12 Feb 2021
Recent advances in deep learning theory
Recent advances in deep learning theory
Fengxiang He
Dacheng Tao
AI4CE
130
51
0
20 Dec 2020
Fair for All: Best-effort Fairness Guarantees for Classification
Fair for All: Best-effort Fairness Guarantees for Classification
A. Krishnaswamy
Zhihao Jiang
Kangning Wang
Yu Cheng
Kamesh Munagala
FaML
180
10
0
18 Dec 2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and
  Using Uncertainty
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
Umang Bhatt
Javier Antorán
Yunfeng Zhang
Q. V. Liao
P. Sattigeri
...
L. Nachman
R. Chunara
Madhulika Srikumar
Adrian Weller
Alice Xiang
129
252
0
15 Nov 2020
Debiasing classifiers: is reality at variance with expectation?
Debiasing classifiers: is reality at variance with expectation?
Ashrya Agrawal
Florian Pfisterer
B. Bischl
Francois Buet-Golfouse
Srijan Sood
Jiahao Chen
Sameena Shah
Sebastian J. Vollmer
CMLFaML
36
18
0
04 Nov 2020
CryptoCredit: Securely Training Fair Models
CryptoCredit: Securely Training Fair Models
Leo de Castro
Jiahao Chen
Antigoni Polychroniadou
47
3
0
09 Oct 2020
On the Identification of Fair Auditors to Evaluate Recommender Systems
  based on a Novel Non-Comparative Fairness Notion
On the Identification of Fair Auditors to Evaluate Recommender Systems based on a Novel Non-Comparative Fairness Notion
Mukund Telukunta
Venkata Sriram Siddhardh Nadendla
FaML
23
0
0
09 Sep 2020
Learning Unbiased Representations via Rényi Minimization
Learning Unbiased Representations via Rényi Minimization
Vincent Grari
Oualid El Hajouji
Sylvain Lamprier
Marcin Detyniecki
FaML
63
21
0
07 Sep 2020
Adversarial Learning for Counterfactual Fairness
Adversarial Learning for Counterfactual Fairness
Vincent Grari
Sylvain Lamprier
Marcin Detyniecki
FaML
57
23
0
30 Aug 2020
Distributionally Robust Losses for Latent Covariate Mixtures
Distributionally Robust Losses for Latent Covariate Mixtures
John C. Duchi
Tatsunori Hashimoto
Hongseok Namkoong
77
81
0
28 Jul 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
147
339
0
23 Jun 2020
Probabilistic Fair Clustering
Probabilistic Fair Clustering
Seyed-Alireza Esmaeili
Brian Brubach
Leonidas Tsepenekas
John P. Dickerson
FaML
78
37
0
19 Jun 2020
Fairness-Aware Explainable Recommendation over Knowledge Graphs
Fairness-Aware Explainable Recommendation over Knowledge Graphs
Zuohui Fu
Yikun Xian
Ruoyuan Gao
Jieyu Zhao
Qiaoying Huang
...
Shuyuan Xu
Shijie Geng
C. Shah
Yongfeng Zhang
Gerard de Melo
FaML
126
208
0
03 Jun 2020
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