ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1711.05144
  4. Cited By
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup
  Fairness
v1v2v3v4v5 (latest)

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

14 November 2017
Michael Kearns
Seth Neel
Aaron Roth
Zhiwei Steven Wu
    FaML
ArXiv (abs)PDFHTML

Papers citing "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness"

50 / 448 papers shown
Title
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
193
10
0
18 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
...
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
OOD
355
1,452
0
14 Dec 2020
FairOD: Fairness-aware Outlier Detection
FairOD: Fairness-aware Outlier Detection
Shubhranshu Shekhar
Neil Shah
Leman Akoglu
82
37
0
05 Dec 2020
Outcome Indistinguishability
Outcome Indistinguishability
Cynthia Dwork
Michael P. Kim
Omer Reingold
G. Rothblum
G. Yona
82
68
0
26 Nov 2020
FairLens: Auditing Black-box Clinical Decision Support Systems
FairLens: Auditing Black-box Clinical Decision Support Systems
Cecilia Panigutti
Alan Perotti
Andre' Panisson
P. Bajardi
D. Pedreschi
96
70
0
08 Nov 2020
Minimax Group Fairness: Algorithms and Experiments
Minimax Group Fairness: Algorithms and Experiments
Emily Diana
Wesley Gill
Michael Kearns
K. Kenthapadi
Aaron Roth
FaMLFedML
80
23
0
05 Nov 2020
Minimax Pareto Fairness: A Multi Objective Perspective
Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martínez
Martín Bertrán
Guillermo Sapiro
FaML
98
197
0
03 Nov 2020
Fair Classification with Group-Dependent Label Noise
Fair Classification with Group-Dependent Label Noise
Jialu Wang
Yang Liu
Caleb C. Levy
NoLa
97
104
0
31 Oct 2020
One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification
One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification
Kenji Kobayashi
Yuri Nakao
FaML
96
8
0
26 Oct 2020
Value Cards: An Educational Toolkit for Teaching Social Impacts of
  Machine Learning through Deliberation
Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation
Hong Shen
Wesley Hanwen Deng
Aditi Chattopadhyay
Zhiwei Steven Wu
Xu Wang
Haiyi Zhu
94
65
0
22 Oct 2020
Environment Inference for Invariant Learning
Environment Inference for Invariant Learning
Elliot Creager
J. Jacobsen
R. Zemel
OOD
114
386
0
14 Oct 2020
Equitable Allocation of Healthcare Resources with Fair Cox Models
Equitable Allocation of Healthcare Resources with Fair Cox Models
Kamrun Naher Keya
Rashidul Islam
Shimei Pan
I. Stockwell
James R. Foulds
50
10
0
14 Oct 2020
Chasing Your Long Tails: Differentially Private Prediction in Health
  Care Settings
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings
Vinith Suriyakumar
Nicolas Papernot
Anna Goldenberg
Marzyeh Ghassemi
OOD
76
67
0
13 Oct 2020
Large-Scale Methods for Distributionally Robust Optimization
Large-Scale Methods for Distributionally Robust Optimization
Daniel Levy
Y. Carmon
John C. Duchi
Aaron Sidford
107
217
0
12 Oct 2020
Metrics and methods for a systematic comparison of fairness-aware
  machine learning algorithms
Metrics and methods for a systematic comparison of fairness-aware machine learning algorithms
Gareth Jones
James M. Hickey
Pietro G. Di Stefano
C. Dhanjal
Laura C. Stoddart
V. Vasileiou
FaML
60
21
0
08 Oct 2020
The Short Anthropological Guide to the Study of Ethical AI
The Short Anthropological Guide to the Study of Ethical AI
Alexandrine Royer
SyDa
18
0
0
07 Oct 2020
Fairness Perception from a Network-Centric Perspective
Fairness Perception from a Network-Centric Perspective
Farzan Masrour
P. Tan
A. Esfahanian
FaML
42
2
0
07 Oct 2020
Fairness in Machine Learning: A Survey
Fairness in Machine Learning: A Survey
Simon Caton
C. Haas
FaML
118
656
0
04 Oct 2020
Group Fairness by Probabilistic Modeling with Latent Fair Decisions
Group Fairness by Probabilistic Modeling with Latent Fair Decisions
YooJung Choi
Meihua Dang
Guy Van den Broeck
FaML
87
33
0
18 Sep 2020
A Framework for Fairer Machine Learning in Organizations
A Framework for Fairer Machine Learning in Organizations
Lily Morse
M. Teodorescu
Yazeed Awwad
Gerald C. Kane
FaMLFedML
37
5
0
10 Sep 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
30
0
0
09 Sep 2020
"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware
  Recommendation
"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware Recommendation
Nasim Sonboli
Robin Burke
Nicholas Mattei
Farzad Eskandanian
Tian Gao
FaML
30
12
0
05 Sep 2020
Fairness in the Eyes of the Data: Certifying Machine-Learning Models
Fairness in the Eyes of the Data: Certifying Machine-Learning Models
Shahar Segal
Yossi Adi
Benny Pinkas
Carsten Baum
C. Ganesh
Joseph Keshet
FedML
72
37
0
03 Sep 2020
Adversarial Learning for Counterfactual Fairness
Adversarial Learning for Counterfactual Fairness
Vincent Grari
Sylvain Lamprier
Marcin Detyniecki
FaML
67
23
0
30 Aug 2020
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Conformal Prediction Sets
R. Berk
Arun K. Kuchibhotla
58
5
0
26 Aug 2020
Beyond Individual and Group Fairness
Beyond Individual and Group Fairness
Pranjal Awasthi
Corinna Cortes
Yishay Mansour
M. Mohri
FaML
149
22
0
21 Aug 2020
Moment Multicalibration for Uncertainty Estimation
Moment Multicalibration for Uncertainty Estimation
Christopher Jung
Changhwa Lee
Mallesh M. Pai
Aaron Roth
R. Vohra
UQCV
245
66
0
18 Aug 2020
Deep F-measure Maximization for End-to-End Speech Understanding
Deep F-measure Maximization for End-to-End Speech Understanding
Leda Sari
M. Hasegawa-Johnson
FedML
33
0
0
08 Aug 2020
Distributionally Robust Losses for Latent Covariate Mixtures
Distributionally Robust Losses for Latent Covariate Mixtures
John C. Duchi
Tatsunori Hashimoto
Hongseok Namkoong
88
81
0
28 Jul 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk
  Prediction
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction
Stephen Pfohl
Agata Foryciarz
N. Shah
FaML
129
115
0
20 Jul 2020
Towards causal benchmarking of bias in face analysis algorithms
Towards causal benchmarking of bias in face analysis algorithms
Guha Balakrishnan
Yuanjun Xiong
Wei Xia
Pietro Perona
CVBM
77
90
0
13 Jul 2020
Ensuring Fairness Beyond the Training Data
Ensuring Fairness Beyond the Training Data
Debmalya Mandal
Samuel Deng
Suman Jana
Jeannette M. Wing
Daniel J. Hsu
FaMLOOD
88
59
0
12 Jul 2020
New Oracle-Efficient Algorithms for Private Synthetic Data Release
New Oracle-Efficient Algorithms for Private Synthetic Data Release
G. Vietri
Grace Tian
Mark Bun
Thomas Steinke
Zhiwei Steven Wu
SyDa
175
77
0
10 Jul 2020
Machine learning fairness notions: Bridging the gap with real-world
  applications
Machine learning fairness notions: Bridging the gap with real-world applications
K. Makhlouf
Sami Zhioua
C. Palamidessi
FaML
68
55
0
30 Jun 2020
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness
Mikhail Yurochkin
Yuekai Sun
FaML
89
50
0
25 Jun 2020
Fairness with Overlapping Groups
Fairness with Overlapping Groups
Forest Yang
Moustapha Cissé
Oluwasanmi Koyejo
FaML
61
22
0
24 Jun 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
153
340
0
23 Jun 2020
Fair Performance Metric Elicitation
Fair Performance Metric Elicitation
Gaurush Hiranandani
Harikrishna Narasimhan
Oluwasanmi Koyejo
75
18
0
23 Jun 2020
Distributional Individual Fairness in Clustering
Distributional Individual Fairness in Clustering
Nihesh Anderson
S. Bera
Syamantak Das
Yang Liu
FedMLFaML
68
21
0
22 Jun 2020
How fair can we go in machine learning? Assessing the boundaries of
  fairness in decision trees
How fair can we go in machine learning? Assessing the boundaries of fairness in decision trees
Ana Valdivia
Javier Sánchez-Monedero
J. Casillas
FaML
75
46
0
22 Jun 2020
Individual Calibration with Randomized Forecasting
Individual Calibration with Randomized Forecasting
Shengjia Zhao
Tengyu Ma
Stefano Ermon
102
60
0
18 Jun 2020
LimeOut: An Ensemble Approach To Improve Process Fairness
LimeOut: An Ensemble Approach To Improve Process Fairness
Vaishnavi Bhargava
Miguel Couceiro
A. Napoli
FaML
74
21
0
17 Jun 2020
Learning Smooth and Fair Representations
Learning Smooth and Fair Representations
Xavier Gitiaux
Huzefa Rangwala
FaML
66
15
0
15 Jun 2020
Causal intersectionality for fair ranking
Causal intersectionality for fair ranking
Ke Yang
Joshua R. Loftus
Julia Stoyanovich
71
41
0
15 Jun 2020
Fairness Under Feature Exemptions: Counterfactual and Observational
  Measures
Fairness Under Feature Exemptions: Counterfactual and Observational Measures
Sanghamitra Dutta
Praveen Venkatesh
Piotr (Peter) Mardziel
Anupam Datta
P. Grover
63
17
0
14 Jun 2020
Analysis of Trade-offs in Fair Principal Component Analysis Based on
  Multi-objective Optimization
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective Optimization
G. D. Pelegrina
Renan D. B. Brotto
L. Duarte
R. Attux
João Marcos Travassos Romano
49
4
0
11 Jun 2020
Probably Approximately Correct Constrained Learning
Probably Approximately Correct Constrained Learning
Luiz F. O. Chamon
Alejandro Ribeiro
80
42
0
09 Jun 2020
Fair Bayesian Optimization
Fair Bayesian Optimization
Valerio Perrone
Michele Donini
Muhammad Bilal Zafar
Robin Schmucker
K. Kenthapadi
Cédric Archambeau
FaML
85
86
0
09 Jun 2020
A Notion of Individual Fairness for Clustering
A Notion of Individual Fairness for Clustering
Matthäus Kleindessner
Pranjal Awasthi
Jamie Morgenstern
FaML
88
30
0
08 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning
Review of Mathematical frameworks for Fairness in Machine Learning
E. del Barrio
Paula Gordaliza
Jean-Michel Loubes
FaMLFedML
71
40
0
26 May 2020
Previous
123456789
Next