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Assessing Algorithmic Fairness with Unobserved Protected Class Using
  Data Combination
v1v2 (latest)

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

1 June 2019
Nathan Kallus
Xiaojie Mao
Angela Zhou
    FaML
ArXiv (abs)PDFHTML

Papers citing "Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination"

40 / 40 papers shown
Title
Preserving AUC Fairness in Learning with Noisy Protected Groups
Preserving AUC Fairness in Learning with Noisy Protected Groups
Mingyang Wu
Li Lin
Wenbin Zhang
Xin Wang
Zhenhuan Yang
Shu Hu
NoLa
160
2
0
24 May 2025
The Impossibility of Fair LLMs
The Impossibility of Fair LLMs
Jacy Reese Anthis
Kristian Lum
Michael Ekstrand
Avi Feller
Alexander D’Amour
FaML
130
14
0
28 May 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
Estimating and Implementing Conventional Fairness Metrics With
  Probabilistic Protected Features
Estimating and Implementing Conventional Fairness Metrics With Probabilistic Protected Features
Hadi Elzayn
Emily Black
Patrick Vossler
Nathanael Jo
Jacob Goldin
Daniel E. Ho
47
5
0
02 Oct 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
68
9
0
03 Nov 2022
Fair admission risk prediction with proportional multicalibration
Fair admission risk prediction with proportional multicalibration
William La Cava
Elle Lett
Guangya Wan
87
8
0
29 Sep 2022
Inference on Strongly Identified Functionals of Weakly Identified
  Functions
Inference on Strongly Identified Functionals of Weakly Identified Functions
Andrew Bennett
Nathan Kallus
Xiaojie Mao
Whitney Newey
Vasilis Syrgkanis
Masatoshi Uehara
114
17
0
17 Aug 2022
Algorithmic Fairness in Business Analytics: Directions for Research and
  Practice
Algorithmic Fairness in Business Analytics: Directions for Research and Practice
Maria De-Arteaga
Stefan Feuerriegel
M. Saar-Tsechansky
FaML
126
45
0
22 Jul 2022
Achievement and Fragility of Long-term Equitability
Achievement and Fragility of Long-term Equitability
Andrea Simonetto
Ivano Notarnicola
55
1
0
24 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
81
23
0
20 May 2022
Gender and Racial Stereotype Detection in Legal Opinion Word Embeddings
Gender and Racial Stereotype Detection in Legal Opinion Word Embeddings
S. Matthews
John Stephen Hudzina
Dawn Sepehr
AILawFaML
61
13
0
24 Mar 2022
Fairness-aware Online Price Discrimination with Nonparametric Demand
  Models
Fairness-aware Online Price Discrimination with Nonparametric Demand Models
Xi Chen
Jiameng Lyu
Xuan Zhang
Yuanshuo Zhou
55
7
0
16 Nov 2021
Fair Sequential Selection Using Supervised Learning Models
Fair Sequential Selection Using Supervised Learning Models
Mohammad Mahdi Khalili
Xueru Zhang
Mahed Abroshan
FaML
60
20
0
26 Oct 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
Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making
Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making
Yi Yang
Ying Nian Wu
Mei Li
Xiangyu Chang
Yong Tan
FaML
51
0
0
21 Sep 2021
Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in
  Practice
Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in Practice
Jiahao Chen
Victor Storchan
Eren Kurshan
50
11
0
11 Aug 2021
Estimation of Fair Ranking Metrics with Incomplete Judgments
Estimation of Fair Ranking Metrics with Incomplete Judgments
Ömer Kirnap
Fernando Diaz
Asia J. Biega
Michael D. Ekstrand
Ben Carterette
Emine Yilmaz
68
38
0
11 Aug 2021
Interactive Storytelling for Children: A Case-study of Design and
  Development Considerations for Ethical Conversational AI
Interactive Storytelling for Children: A Case-study of Design and Development Considerations for Ethical Conversational AI
J. Chubb
S. Missaoui
S. Concannon
Liam Maloney
James Alfred Walker
49
35
0
20 Jul 2021
Auditing for Diversity using Representative Examples
Auditing for Diversity using Representative Examples
Vijay Keswani
L. E. Celis
69
3
0
15 Jul 2021
Multiaccurate Proxies for Downstream Fairness
Multiaccurate Proxies for Downstream Fairness
Emily Diana
Wesley Gill
Michael Kearns
K. Kenthapadi
Aaron Roth
Saeed Sharifi-Malvajerdi
82
22
0
09 Jul 2021
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training
  Data
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data
Eugenia Iofinova
Nikola Konstantinov
Christoph H. Lampert
FaML
94
0
0
22 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
Fairness-Aware Unsupervised Feature Selection
Fairness-Aware Unsupervised Feature Selection
Xiaoying Xing
Hongfu Liu
Chen Chen
Jundong Li
FaML
72
14
0
04 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
Robust Classification via Support Vector Machines
Robust Classification via Support Vector Machines
Vali Asimit
I. Kyriakou
Simone Santoni
Salvatore Scognamiglio
Rui Zhu
AAMLOOD
23
3
0
27 Apr 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
Removing biased data to improve fairness and accuracy
Removing biased data to improve fairness and accuracy
Sahil Verma
Michael Ernst
René Just
FaML
123
25
0
05 Feb 2021
A Statistical Test for Probabilistic Fairness
A Statistical Test for Probabilistic Fairness
Bahar Taşkesen
Jose H. Blanchet
Daniel Kuhn
Viet Anh Nguyen
FaML
76
41
0
09 Dec 2020
Improving Fairness and Privacy in Selection Problems
Improving Fairness and Privacy in Selection Problems
Mohammad Mahdi Khalili
Xueru Zhang
Mahed Abroshan
Somayeh Sojoudi
147
27
0
07 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
132
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
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
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers
  for Welfare-Aware Machine Learning
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
Esther Rolf
Max Simchowitz
Sarah Dean
Lydia T. Liu
Daniel Björkegren
Moritz Hardt
J. Blumenstock
43
23
0
15 Mar 2020
Fair Learning with Private Demographic Data
Fair Learning with Private Demographic Data
Hussein Mozannar
Mesrob I. Ohannessian
Nathan Srebro
94
76
0
26 Feb 2020
Robust Optimization for Fairness with Noisy Protected Groups
Robust Optimization for Fairness with Noisy Protected Groups
S. Wang
Wenshuo Guo
Harikrishna Narasimhan
Andrew Cotter
Maya R. Gupta
Michael I. Jordan
NoLa
76
122
0
21 Feb 2020
Algorithmic Fairness
Algorithmic Fairness
Dana Pessach
E. Shmueli
FaML
102
395
0
21 Jan 2020
Localized Debiased Machine Learning: Efficient Inference on Quantile
  Treatment Effects and Beyond
Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond
Nathan Kallus
Xiaojie Mao
Masatoshi Uehara
73
27
0
30 Dec 2019
Fairness in Deep Learning: A Computational Perspective
Fairness in Deep Learning: A Computational Perspective
Mengnan Du
Fan Yang
Na Zou
Helen Zhou
FaMLFedML
66
234
0
23 Aug 2019
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