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Fairness in Machine Learning: A Survey

Fairness in Machine Learning: A Survey

4 October 2020
Simon Caton
C. Haas
    FaML
ArXivPDFHTML

Papers citing "Fairness in Machine Learning: A Survey"

50 / 82 papers shown
Title
Facets of Disparate Impact: Evaluating Legally Consistent Bias in Machine Learning
Facets of Disparate Impact: Evaluating Legally Consistent Bias in Machine Learning
Jarren Briscoe
Assefaw Gebremedhin
FaML
87
3
0
08 May 2025
Causally Fair Node Classification on Non-IID Graph Data
Causally Fair Node Classification on Non-IID Graph Data
Yucong Dai
Lu Zhang
Yaowei Hu
Susan Gauch
Yongkai Wu
FaML
45
0
0
03 May 2025
Machine Learning Fairness in House Price Prediction: A Case Study of America's Expanding Metropolises
Machine Learning Fairness in House Price Prediction: A Case Study of America's Expanding Metropolises
Abdalwahab Almajed
Maryam Tabar
Peyman Najafirad
AI4TS
26
0
0
02 May 2025
Intersectional Divergence: Measuring Fairness in Regression
Intersectional Divergence: Measuring Fairness in Regression
Joe Germino
Nuno Moniz
Nitesh V. Chawla
FaML
63
0
0
01 May 2025
Mitigating Bias in Facial Recognition Systems: Centroid Fairness Loss Optimization
Mitigating Bias in Facial Recognition Systems: Centroid Fairness Loss Optimization
Jean-Rémy Conti
Stéphan Clémençon
12
0
0
27 Apr 2025
Class-Conditional Distribution Balancing for Group Robust Classification
Class-Conditional Distribution Balancing for Group Robust Classification
Miaoyun Zhao
Qiang Zhang
C. Li
64
1
0
24 Apr 2025
Attention IoU: Examining Biases in CelebA using Attention Maps
Attention IoU: Examining Biases in CelebA using Attention Maps
Aaron Serianni
Tyler Zhu
Olga Russakovsky
V. V. Ramaswamy
39
0
0
25 Mar 2025
Fair Text Classification via Transferable Representations
Thibaud Leteno
Michael Perrot
Charlotte Laclau
Antoine Gourru
Christophe Gravier
FaML
83
0
0
10 Mar 2025
Knowledge Augmentation in Federation: Rethinking What Collaborative Learning Can Bring Back to Decentralized Data
Wentai Wu
Ligang He
Saiqin Long
Ahmed M. Abdelmoniem
Yingliang Wu
Rui Mao
55
0
0
05 Mar 2025
Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue Optimization
Junhui Shen
Aaron J. Davis
Ding Lu
Z. Bai
32
1
0
01 Mar 2025
Investigating the Relationship Between Debiasing and Artifact Removal using Saliency Maps
Investigating the Relationship Between Debiasing and Artifact Removal using Saliency Maps
Lukasz Sztukiewicz
Ignacy Stepka
Michał Wiliński
Jerzy Stefanowski
31
0
0
28 Feb 2025
Testing for Causal Fairness
Testing for Causal Fairness
Jiarun Fu
LiZhong Ding
Pengqi Li
Qiuning Wei
Yurong Cheng
Xu Chen
44
0
0
18 Feb 2025
Targeted Learning for Data Fairness
Targeted Learning for Data Fairness
Alexander Asemota
Giles Hooker
FaML
91
0
0
06 Feb 2025
A Fairness-Oriented Reinforcement Learning Approach for the Operation and Control of Shared Micromobility Services
A Fairness-Oriented Reinforcement Learning Approach for the Operation and Control of Shared Micromobility Services
Luca Vittorio Piron
Matteo Cederle
Marina Ceccon
Federico Chiariotti
Alessandro Fabris
Marco Fabris
Gian Antonio Susto
42
0
0
20 Jan 2025
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
Jitao Wang
C. Shi
John D. Piette
Joshua R. Loftus
Donglin Zeng
Zhenke Wu
OffRL
61
0
0
10 Jan 2025
Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
Adam Wang
Son Nguyen
A. Montillo
FedML
41
0
0
31 Dec 2024
Towards Efficient and Explainable Hate Speech Detection via Model
  Distillation
Towards Efficient and Explainable Hate Speech Detection via Model Distillation
Paloma Piot
Javier Parapar
78
173
0
18 Dec 2024
Fair Resource Allocation in Weakly Coupled Markov Decision Processes
Fair Resource Allocation in Weakly Coupled Markov Decision Processes
Xiaohui Tu
Yossiri Adulyasak
Nima Akbarzadeh
Erick Delage
39
0
0
14 Nov 2024
Properties of fairness measures in the context of varying class imbalance and protected group ratios
Properties of fairness measures in the context of varying class imbalance and protected group ratios
D. Brzezinski
Julia Stachowiak
Jerzy Stefanowski
Izabela Szczech
R. Susmaga
Sofya Aksenyuk
Uladzimir Ivashka
Oleksandr Yasinskyi
131
4
0
13 Nov 2024
A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning
A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning
Caleb J. S. Barr
Olivia Erdelyi
Paul D. Docherty
Randolph C. Grace
FaML
65
0
0
10 Nov 2024
Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation
Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation
To Eun Kim
Fernando Diaz
51
2
0
17 Sep 2024
Fairness-Aware Meta-Learning via Nash Bargaining
Fairness-Aware Meta-Learning via Nash Bargaining
Yi Zeng
Xuelin Yang
Li Chen
Cristian Canton Ferrer
Ming Jin
Michael I. Jordan
Ruoxi Jia
37
2
0
11 Jun 2024
Addressing Discretization-Induced Bias in Demographic Prediction
Addressing Discretization-Induced Bias in Demographic Prediction
Evan Dong
Aaron Schein
Yixin Wang
Nikhil Garg
32
3
0
27 May 2024
Learning Social Fairness Preferences from Non-Expert Stakeholder
  Opinions in Kidney Placement
Learning Social Fairness Preferences from Non-Expert Stakeholder Opinions in Kidney Placement
Mukund Telukunta
Sukruth Rao
Gabriella Stickney
Venkata Sriram Siddhardh Nadendla
Casey Canfield
28
1
0
04 Apr 2024
Beyond RMSE and MAE: Introducing EAUC to unmask hidden bias and unfairness in dyadic regression models
Beyond RMSE and MAE: Introducing EAUC to unmask hidden bias and unfairness in dyadic regression models
Jorge Paz-Ruza
Amparo Alonso-Betanzos
B. Guijarro-Berdiñas
Brais Cancela
Carlos Eiras-Franco
51
2
0
19 Jan 2024
Fair Supervised Learning with A Simple Random Sampler of Sensitive
  Attributes
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes
Jinwon Sohn
Qifan Song
Guang Lin
FaML
34
1
0
10 Nov 2023
Marginal Nodes Matter: Towards Structure Fairness in Graphs
Marginal Nodes Matter: Towards Structure Fairness in Graphs
Xiaotian Han
Kaixiong Zhou
Ting-Hsiang Wang
Jundong Li
Fei Wang
Na Zou
27
0
0
23 Oct 2023
On Prediction-Modelers and Decision-Makers: Why Fairness Requires More
  Than a Fair Prediction Model
On Prediction-Modelers and Decision-Makers: Why Fairness Requires More Than a Fair Prediction Model
Teresa Scantamburlo
Joachim Baumann
Christoph Heitz
FaML
31
3
0
09 Oct 2023
On The Impact of Machine Learning Randomness on Group Fairness
On The Impact of Machine Learning Randomness on Group Fairness
Prakhar Ganesh
Hong Chang
Martin Strobel
Reza Shokri
FaML
21
30
0
09 Jul 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
On Performance Discrepancies Across Local Homophily Levels in Graph
  Neural Networks
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks
Donald Loveland
Jiong Zhu
Mark Heimann
Benjamin Fish
Michael T. Shaub
Danai Koutra
30
5
0
08 Jun 2023
On the Origins of Bias in NLP through the Lens of the Jim Code
On the Origins of Bias in NLP through the Lens of the Jim Code
Fatma Elsafoury
Gavin Abercrombie
34
4
0
16 May 2023
A Classification of Feedback Loops and Their Relation to Biases in
  Automated Decision-Making Systems
A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems
Nicolò Pagan
Joachim Baumann
Ezzat Elokda
Giulia De Pasquale
S. Bolognani
Anikó Hannák
29
23
0
10 May 2023
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or
  Why the Law is not a Decision Tree
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree
Hilde J. P. Weerts
Raphaële Xenidis
Fabien Tarissan
Henrik Palmer Olsen
Mykola Pechenizkiy
FaML
22
21
0
05 May 2023
Auditing ICU Readmission Rates in an Clinical Database: An Analysis of
  Risk Factors and Clinical Outcomes
Auditing ICU Readmission Rates in an Clinical Database: An Analysis of Risk Factors and Clinical Outcomes
Shaina Raza
19
4
0
12 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
Connecting Fairness in Machine Learning with Public Health Equity
Connecting Fairness in Machine Learning with Public Health Equity
Shaina Raza
13
5
0
08 Apr 2023
Fairness-Aware Data Valuation for Supervised Learning
Fairness-Aware Data Valuation for Supervised Learning
José P. Pombal
Pedro Saleiro
Mário A. T. Figueiredo
P. Bizarro
TDI
35
3
0
29 Mar 2023
Beyond Accuracy: A Critical Review of Fairness in Machine Learning for
  Mobile and Wearable Computing
Beyond Accuracy: A Critical Review of Fairness in Machine Learning for Mobile and Wearable Computing
Sofia Yfantidou
Marios Constantinides
Dimitris Spathis
Athena Vakali
Daniele Quercia
F. Kawsar
HAI
FaML
26
18
0
27 Mar 2023
Travel Demand Forecasting: A Fair AI Approach
Travel Demand Forecasting: A Fair AI Approach
Xiaojian Zhang
Qian Ke
Xilei Zhao
AI4TS
13
2
0
03 Mar 2023
Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning
Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning
Sirui Ding
Ruixiang Tang
Daochen Zha
Na Zou
Kai Zhang
Xiaoqian Jiang
Xia Hu
21
9
0
18 Feb 2023
Fair Spatial Indexing: A paradigm for Group Spatial Fairness
Fair Spatial Indexing: A paradigm for Group Spatial Fairness
Sina shaham
Gabriel Ghinita
Cyrus Shahabi
20
0
0
05 Feb 2023
Vertical Federated Learning: Taxonomies, Threats, and Prospects
Vertical Federated Learning: Taxonomies, Threats, and Prospects
Qun Li
Chandra Thapa
Lawrence Ong
Yifeng Zheng
Hua Ma
S. Çamtepe
Anmin Fu
Yan Gao
FedML
36
10
0
03 Feb 2023
Entropy-driven Fair and Effective Federated Learning
Entropy-driven Fair and Effective Federated Learning
Lung-Chuang Wang
Zhichao Wang
Sai Praneeth Karimireddy
Xiaoying Tang
Xiaoying Tang
FedML
33
9
0
29 Jan 2023
Discovering and Mitigating Visual Biases through Keyword Explanation
Discovering and Mitigating Visual Biases through Keyword Explanation
Younghyun Kim
Sangwoo Mo
Minkyu Kim
Kyungmin Lee
Jaeho Lee
Jinwoo Shin
34
30
0
26 Jan 2023
Fairness Increases Adversarial Vulnerability
Fairness Increases Adversarial Vulnerability
Cuong Tran
Keyu Zhu
Ferdinando Fioretto
Pascal Van Hentenryck
18
6
0
21 Nov 2022
Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning
Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning
Qingquan Zhang
Jialin Liu
Zeqi Zhang
J. Wen
Bifei Mao
Xin Yao
FaML
40
17
0
30 Oct 2022
Group Fairness in Prediction-Based Decision Making: From Moral
  Assessment to Implementation
Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation
Joachim Baumann
Christoph Heitz
21
8
0
19 Oct 2022
FAIR-FATE: Fair Federated Learning with Momentum
FAIR-FATE: Fair Federated Learning with Momentum
Teresa Salazar
Miguel X. Fernandes
Helder Araújo
Pedro Abreu
FedML
30
18
0
27 Sep 2022
Explainable Global Fairness Verification of Tree-Based Classifiers
Explainable Global Fairness Verification of Tree-Based Classifiers
Stefano Calzavara
Lorenzo Cazzaro
Claudio Lucchese
Federico Marcuzzi
24
2
0
27 Sep 2022
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