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Retiring Adult: New Datasets for Fair Machine Learning

Retiring Adult: New Datasets for Fair Machine Learning

10 August 2021
Frances Ding
Moritz Hardt
John Miller
Ludwig Schmidt
ArXivPDFHTML

Papers citing "Retiring Adult: New Datasets for Fair Machine Learning"

50 / 288 papers shown
Title
Correcting Underrepresentation and Intersectional Bias for
  Classification
Correcting Underrepresentation and Intersectional Bias for Classification
Emily Diana
A. Tolbert
FaML
21
1
0
19 Jun 2023
Fairness in Multi-Task Learning via Wasserstein Barycenters
Fairness in Multi-Task Learning via Wasserstein Barycenters
Franccois Hu
Philipp Ratz
Arthur Charpentier
35
10
0
16 Jun 2023
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
Xiaotian Han
Jianfeng Chi
Yu Chen
Qifan Wang
Han Zhao
Na Zou
Xia Hu
44
25
0
15 Jun 2023
Questioning the Survey Responses of Large Language Models
Questioning the Survey Responses of Large Language Models
Ricardo Dominguez-Olmedo
Moritz Hardt
Celestine Mendler-Dünner
26
30
0
13 Jun 2023
Unprocessing Seven Years of Algorithmic Fairness
Unprocessing Seven Years of Algorithmic Fairness
André F. Cruz
Moritz Hardt
29
10
0
12 Jun 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
FedVal: Different good or different bad in federated learning
FedVal: Different good or different bad in federated learning
Viktor Valadi
Xinchi Qiu
Pedro Gusmão
Nicholas D. Lane
Mina Alibeigi
FedML
AAML
12
2
0
06 Jun 2023
Generating Private Synthetic Data with Genetic Algorithms
Generating Private Synthetic Data with Genetic Algorithms
Terrance Liu
Jin-Lin Tang
G. Vietri
Zhiwei Steven Wu
SyDa
19
16
0
05 Jun 2023
Affinity Clustering Framework for Data Debiasing Using Pairwise
  Distribution Discrepancy
Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy
Siamak Ghodsi
Eirini Ntoutsi
17
1
0
02 Jun 2023
Adapting Fairness Interventions to Missing Values
Adapting Fairness Interventions to Missing Values
R. Feng
Flavio du Pin Calmon
Hao Wang
FaML
26
9
0
30 May 2023
Auditing Fairness by Betting
Auditing Fairness by Betting
Ben Chugg
Santiago Cortes-Gomez
Bryan Wilder
Aaditya Ramdas
MLAU
45
7
0
27 May 2023
Mitigating Group Bias in Federated Learning: Beyond Local Fairness
Mitigating Group Bias in Federated Learning: Beyond Local Fairness
G. Wang
Ali Payani
Myungjin Lee
Ramana Rao Kompella
FedML
38
8
0
17 May 2023
WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and
  Democratic is FAccT?
WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT?
Ali Akbar Septiandri
Marios Constantinides
Mohammad Tahaei
Daniele Quercia
25
34
0
10 May 2023
Causal Information Splitting: Engineering Proxy Features for Robustness
  to Distribution Shifts
Causal Information Splitting: Engineering Proxy Features for Robustness to Distribution Shifts
Bijan Mazaheri
Atalanti Mastakouri
Dominik Janzing
Mila Hardt
OOD
35
3
0
10 May 2023
Statistical Inference for Fairness Auditing
Statistical Inference for Fairness Auditing
John J. Cherian
Emmanuel J. Candès
MLAU
40
8
0
05 May 2023
(Local) Differential Privacy has NO Disparate Impact on Fairness
(Local) Differential Privacy has NO Disparate Impact on Fairness
Héber H. Arcolezi
K. Makhlouf
C. Palamidessi
40
6
0
25 Apr 2023
Individual Fairness in Bayesian Neural Networks
Individual Fairness in Bayesian Neural Networks
Alice Doherty
Matthew Wicker
Luca Laurenti
A. Patané
24
5
0
21 Apr 2023
The Dataset Multiplicity Problem: How Unreliable Data Impacts
  Predictions
The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions
Anna P. Meyer
Aws Albarghouthi
Loris Dántoni
22
13
0
20 Apr 2023
Fairness in AI and Its Long-Term Implications on Society
Fairness in AI and Its Long-Term Implications on Society
Ondrej Bohdal
Timothy M. Hospedales
Philip H. S. Torr
Fazl Barez
13
4
0
16 Apr 2023
Learning Optimal Fair Scoring Systems for Multi-Class Classification
Learning Optimal Fair Scoring Systems for Multi-Class Classification
Julien Rouzot
Julien Ferry
Marie-José Huguet
FaML
19
8
0
11 Apr 2023
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural
  Networks
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks
Yuzhen Mao
Zhun Deng
Huaxiu Yao
Ting Ye
Kenji Kawaguchi
James Zou
36
20
0
08 Apr 2023
Non-Invasive Fairness in Learning through the Lens of Data Drift
Non-Invasive Fairness in Learning through the Lens of Data Drift
Ke Yang
A. Meliou
29
0
0
30 Mar 2023
Identification of Negative Transfers in Multitask Learning Using
  Surrogate Models
Identification of Negative Transfers in Multitask Learning Using Surrogate Models
Dongyue Li
Huy Le Nguyen
Hongyang R. Zhang
39
12
0
25 Mar 2023
Data-centric Artificial Intelligence: A Survey
Data-centric Artificial Intelligence: A Survey
Daochen Zha
Zaid Pervaiz Bhat
Kwei-Herng Lai
Fan Yang
Zhimeng Jiang
Shaochen Zhong
Xia Hu
18
192
0
17 Mar 2023
Explaining Groups of Instances Counterfactually for XAI: A Use Case,
  Algorithm and User Study for Group-Counterfactuals
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals
Greta Warren
Markt. Keane
Christophe Guéret
Eoin Delaney
26
13
0
16 Mar 2023
Can Fairness be Automated? Guidelines and Opportunities for
  Fairness-aware AutoML
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML
Hilde J. P. Weerts
Florian Pfisterer
Matthias Feurer
Katharina Eggensperger
Eddie Bergman
Noor H. Awad
Joaquin Vanschoren
Mykola Pechenizkiy
B. Bischl
Frank Hutter
FaML
38
18
0
15 Mar 2023
Explanation Shift: How Did the Distribution Shift Impact the Model?
Explanation Shift: How Did the Distribution Shift Impact the Model?
Carlos Mougan
Klaus Broelemann
David Masip
Gjergji Kasneci
Thanassis Thiropanis
Steffen Staab
FAtt
22
1
0
14 Mar 2023
Beyond Demographic Parity: Redefining Equal Treatment
Beyond Demographic Parity: Redefining Equal Treatment
Carlos Mougan
Laura State
Antonio Ferrara
Salvatore Ruggieri
Steffen Staab
FaML
33
1
0
14 Mar 2023
Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods
Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods
Julien Ferry
Gabriel Laberge
Ulrich Aïvodji
28
5
0
08 Mar 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
Diagnosing Model Performance Under Distribution Shift
Diagnosing Model Performance Under Distribution Shift
Tiffany Cai
Hongseok Namkoong
Steve Yadlowsky
37
27
0
03 Mar 2023
Feature Importance Disparities for Data Bias Investigations
Feature Importance Disparities for Data Bias Investigations
Peter W. Chang
Leor Fishman
Seth Neel
26
2
0
03 Mar 2023
Domain Adaptive Decision Trees: Implications for Accuracy and Fairness
Domain Adaptive Decision Trees: Implications for Accuracy and Fairness
J. Álvarez
Kristen M. Scott
Salvatore Ruggieri
Bettina Berendt
19
6
0
27 Feb 2023
Classification with Trust: A Supervised Approach based on Sequential
  Ellipsoidal Partitioning
Classification with Trust: A Supervised Approach based on Sequential Ellipsoidal Partitioning
Ranjani Niranjan
Sachit Rao
16
1
0
21 Feb 2023
Certified private data release for sparse Lipschitz functions
Certified private data release for sparse Lipschitz functions
Konstantin Donhauser
J. Lokna
Amartya Sanyal
M. Boedihardjo
R. Honig
Fanny Yang
46
3
0
19 Feb 2023
The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance
  Trade-Offs in the Context of Fair Prediction
The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction
Falaah Arif Khan
Julia Stoyanovich
FaML
VLM
CML
6
3
0
17 Feb 2023
The Possibility of Fairness: Revisiting the Impossibility Theorem in
  Practice
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice
Andrew Bell
Lucius E.J. Bynum
Nazarii Drushchak
Tetiana Herasymova
Lucas Rosenblatt
Julia Stoyanovich
41
18
0
13 Feb 2023
Multi-dimensional discrimination in Law and Machine Learning -- A
  comparative overview
Multi-dimensional discrimination in Law and Machine Learning -- A comparative overview
Arjun Roy
J. Horstmann
Eirini Ntoutsi
FaML
15
20
0
12 Feb 2023
On Comparing Fair Classifiers under Data Bias
On Comparing Fair Classifiers under Data Bias
Mohit Sharma
Amit Deshpande
R. Shah
29
2
0
12 Feb 2023
On Fairness and Stability: Is Estimator Variance a Friend or a Foe?
On Fairness and Stability: Is Estimator Variance a Friend or a Foe?
Falaah Arif Khan
Denys Herasymuk
Julia Stoyanovich
33
2
0
09 Feb 2023
Robustness Implies Fairness in Causal Algorithmic Recourse
Robustness Implies Fairness in Causal Algorithmic Recourse
A. Ehyaei
Amir-Hossein Karimi
Bernhard Schölkopf
S. Maghsudi
FaML
33
12
0
07 Feb 2023
RLSbench: Domain Adaptation Under Relaxed Label Shift
RLSbench: Domain Adaptation Under Relaxed Label Shift
Saurabh Garg
Nick Erickson
James Sharpnack
Alexander J. Smola
Sivaraman Balakrishnan
Zachary Chase Lipton
VLM
33
31
0
06 Feb 2023
An Empirical Analysis of Fairness Notions under Differential Privacy
An Empirical Analysis of Fairness Notions under Differential Privacy
Anderson Santana de Oliveira
Caelin Kaplan
Khawla Mallat
Tanmay Chakraborty
FedML
15
7
0
06 Feb 2023
Improving Fair Training under Correlation Shifts
Improving Fair Training under Correlation Shifts
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
32
17
0
05 Feb 2023
An Operational Perspective to Fairness Interventions: Where and How to
  Intervene
An Operational Perspective to Fairness Interventions: Where and How to Intervene
Brian Hsu
Xiaotong Chen
Ying Han
Hongseok Namkoong
Kinjal Basu
24
1
0
03 Feb 2023
On the Within-Group Fairness of Screening Classifiers
On the Within-Group Fairness of Screening Classifiers
Nastaran Okati
Stratis Tsirtsis
Manuel Gomez Rodriguez
22
2
0
31 Jan 2023
Multicalibration as Boosting for Regression
Multicalibration as Boosting for Regression
Ira Globus-Harris
Declan Harrison
Michael Kearns
Aaron Roth
Jessica Sorrell
30
21
0
31 Jan 2023
Retiring $Δ$DP: New Distribution-Level Metrics for Demographic
  Parity
Retiring ΔΔΔDP: New Distribution-Level Metrics for Demographic Parity
Xiaotian Han
Zhimeng Jiang
Hongye Jin
Zirui Liu
Na Zou
Qifan Wang
Xia Hu
35
3
0
31 Jan 2023
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness
  Interventions
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions
Hao Wang
Luxi He
Rui Gao
Flavio du Pin Calmon
19
9
0
27 Jan 2023
Incentives to Offer Algorithmic Recourse
Incentives to Offer Algorithmic Recourse
Matthew Olckers
T. Walsh
26
2
0
27 Jan 2023
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