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Fair Machine Learning

FaML
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Promotes ethical AI by ensuring models are fair, interpretable, and responsible. Addresses biases and builds trust in AI systems.

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50 / 1,626 papers shown
Title
Alternative Fairness and Accuracy Optimization in Criminal Justice
Alternative Fairness and Accuracy Optimization in Criminal Justice
Shaolong Wu
James Blume
Geshi Yeung
FaML
65
0
0
06 Nov 2025
Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
Zhecheng Sheng
Jiawei Zhang
Enmao Diao
FaML
96
0
0
01 Nov 2025
FairAD: Computationally Efficient Fair Graph Clustering via Algebraic Distance
FairAD: Computationally Efficient Fair Graph Clustering via Algebraic Distance
Minh Phu Vuong
Young Ju-Lee
Iván Ojeda-Ruiz
Chul-Ho Lee
FaML
104
0
0
31 Oct 2025
flowengineR: A Modular and Extensible Framework for Fair and Reproducible Workflow Design in R
flowengineR: A Modular and Extensible Framework for Fair and Reproducible Workflow Design in R
Maximilian Willer
Peter Ruckdeschel
FaML
20
0
0
29 Oct 2025
On the Societal Impact of Machine Learning
On the Societal Impact of Machine Learning
Joachim Baumann
FaML
80
0
0
27 Oct 2025
Visual Model Selection using Feature Importance Clusters in Fairness-Performance Similarity Optimized Space
Visual Model Selection using Feature Importance Clusters in Fairness-Performance Similarity Optimized Space
Sofoklis Kitharidis
Cor J. Veenman
Thomas Bäck
Niki van Stein
FaML
81
0
0
25 Oct 2025
Online Multi-Class Selection with Group Fairness Guarantee
Online Multi-Class Selection with Group Fairness Guarantee
Faraz Zargari
Hossein Nekouyan
Lyndon Hallett
Bo Sun
Xiaoqi Tan
FaML
50
0
0
23 Oct 2025
Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
Yuhong Luo
Austin Hoag
Xintong Wang
Philip S Thomas
Przemyslaw A. Grabowicz
FaML
104
0
0
23 Oct 2025
FairGRPO: Fair Reinforcement Learning for Equitable Clinical Reasoning
FairGRPO: Fair Reinforcement Learning for Equitable Clinical Reasoning
Shiqi Dai
Wei Dai
Jiaee Cheong
Paul Liang
FaMLOffRL
52
0
0
22 Oct 2025
FairNet: Dynamic Fairness Correction without Performance Loss via Contrastive Conditional LoRA
FairNet: Dynamic Fairness Correction without Performance Loss via Contrastive Conditional LoRA
Songqi Zhou
Zeyuan Liu
Benben Jiang
FaML
37
0
0
22 Oct 2025
A Justice Lens on Fairness and Ethics Courses in Computing Education: LLM-Assisted Multi-Perspective and Thematic Evaluation
A Justice Lens on Fairness and Ethics Courses in Computing Education: LLM-Assisted Multi-Perspective and Thematic Evaluation
Kenya S. Andrews
Deborah Dormah Kanubala
Kehinde Aruleba
Francisco Enrique Vicente Castro
Renata A Revelo
FaMLAILaw
36
0
0
21 Oct 2025
Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
Valia Efthymiou
Ekaterina Fedorova
Chara Podimata
FaML
36
0
0
21 Oct 2025
Adversary-Free Counterfactual Prediction via Information-Regularized Representations
Adversary-Free Counterfactual Prediction via Information-Regularized Representations
Shiqin Tang
Rong Feng
Shuxin Zhuang
Hongzong Li
Youzhi Zhang
OODFaML
89
0
0
17 Oct 2025
Evidence Without Injustice: A New Counterfactual Test for Fair Algorithms
Evidence Without Injustice: A New Counterfactual Test for Fair Algorithms
Michele Loi
M. Bello
N. Cangiotti
FaMLMLAU
192
0
0
10 Oct 2025
PyCFRL: A Python library for counterfactually fair offline reinforcement learning via sequential data preprocessing
Jianhan Zhang
Jitao Wang
C. Shi
John D. Piette
Donglin Zeng
Zhenke Wu
OffRLFaMLOnRL
77
0
0
08 Oct 2025
Set to Be Fair: Demographic Parity Constraints for Set-Valued Classification
Set to Be Fair: Demographic Parity Constraints for Set-Valued Classification
Eyal Cohen
Christophe Denis
Mohamed Hebiri
FaML
44
0
0
06 Oct 2025
FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
Yucong Dai
Lu Zhang
Feng Luo
M. Chowdhury
Yongkai Wu
FaML
81
0
0
05 Oct 2025
FairContrast: Enhancing Fairness through Contrastive learning and Customized Augmenting Methods on Tabular Data
FairContrast: Enhancing Fairness through Contrastive learning and Customized Augmenting Methods on Tabular Data
Aida Tayebi
Ali Khodabandeh Yalabadi
Mehdi Yazdani-Jahromi
O. Garibay
FaML
80
0
0
02 Oct 2025
MultiFair: Multimodal Balanced Fairness-Aware Medical Classification with Dual-Level Gradient Modulation
MultiFair: Multimodal Balanced Fairness-Aware Medical Classification with Dual-Level Gradient Modulation
Md Zubair
Hao Zheng
Nussdorf Jonathan
Grayson W. Armstrong
Lucy Q. Shen
Gabriela Wilson
Yu Tian
Xingquan Zhu
Min Shi
FaML
44
0
0
30 Sep 2025
Partial Identification Approach to Counterfactual Fairness Assessment
Partial Identification Approach to Counterfactual Fairness Assessment
Saeyoung Rho
Junzhe Zhang
Elias Bareinboim
FaML
48
0
0
30 Sep 2025
Fair Classification by Direct Intervention on Operating Characteristics
Fair Classification by Direct Intervention on Operating Characteristics
Kevin Jiang
Edgar Dobriban
FaML
49
0
0
29 Sep 2025
Accessible, Realistic, and Fair Evaluation of Positive-Unlabeled Learning Algorithms
Accessible, Realistic, and Fair Evaluation of Positive-Unlabeled Learning Algorithms
Wei Wang
Dong-Dong Wu
Ming Li
J. Zhang
Gang Niu
Masashi Sugiyama
FaML
66
0
0
29 Sep 2025
Two-Sided Fairness in Many-to-One Matching
Two-Sided Fairness in Many-to-One Matching
Ayumi Igarashi
Naoyuki Kamiyama
Yasushi Kawase
Warut Suksompong
Hanna Sumita
Yu Yokoi
FaML
52
0
0
28 Sep 2025
Fairness-Aware Reinforcement Learning (FAReL): A Framework for Transparent and Balanced Sequential Decision-Making
Fairness-Aware Reinforcement Learning (FAReL): A Framework for Transparent and Balanced Sequential Decision-Making
Alexandra Cimpean
Nicole Orzan
Catholijn M. Jonker
Pieter J. K. Libin
A. Nowé
FaMLOffRL
48
0
0
26 Sep 2025
Interpretable Network-assisted Random Forest+
Interpretable Network-assisted Random Forest+
Tiffany M. Tang
Elizaveta Levina
Ji Zhu
FaML
24
0
0
19 Sep 2025
On the Regularity and Fairness of Combinatorial Multi-Armed Bandit
On the Regularity and Fairness of Combinatorial Multi-Armed Bandit
Xiaoyi Wu
Bin Li
FaML
100
0
0
15 Sep 2025
Envy-Free but Still Unfair: Envy-Freeness Up To One Item (EF-1) in Personalized Recommendation
Envy-Free but Still Unfair: Envy-Freeness Up To One Item (EF-1) in Personalized Recommendation
Amanda A. Aird
Ben Armstrong
Nicholas Mattei
Robin Burke
FaML
92
0
0
10 Sep 2025
Inference of Altruism and Intrinsic Rewards in Multi-Agent Systems
Inference of Altruism and Intrinsic Rewards in Multi-Agent Systems
Victor Villin
Christos Dimitrakakis
FaML
88
0
0
09 Sep 2025
Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting
Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting
Sai Siddhartha Chary Aylapuram
Veeraraju Elluru
Shivang Agarwal
FaMLMU
65
0
0
09 Sep 2025
Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation
Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation
Ho Ming Lee
Katrien Antonio
Benjamin Avanzi
Lorenzo Marchi
Rui Zhou
FaML
137
1
0
09 Sep 2025
Risk-averse Fair Multi-class Classification
Risk-averse Fair Multi-class Classification
Darinka Dentcheva
Xiangyu Tian
FaML
60
0
0
06 Sep 2025
A Primer on Causal and Statistical Dataset Biases for Fair and Robust Image Analysis
A Primer on Causal and Statistical Dataset Biases for Fair and Robust Image Analysis
Charles Jones
Ben Glocker
CMLFaML
72
0
0
04 Sep 2025
Who Pays for Fairness? Rethinking Recourse under Social Burden
Who Pays for Fairness? Rethinking Recourse under Social Burden
Ainhize Barrainkua
Giovanni De Toni
Jose A. Lozano
Novi Quadrianto
FaML
123
0
0
04 Sep 2025
Fairness for niche users and providers: algorithmic choice and profile portability
Fairness for niche users and providers: algorithmic choice and profile portability
Elizabeth McKinnie
Anas Buhayh
Clement Canel
Robin Burke
FaML
56
0
0
28 Aug 2025
Multistakeholder Fairness in Tourism: What can Algorithms learn from Tourism Management?
Multistakeholder Fairness in Tourism: What can Algorithms learn from Tourism Management?Frontiers in Big Data (FBD), 2025
Peter Muellner
Anna Schreuer
Simone Kopeinik
Bernhard Wieser
Dominik Kowald
FaML
88
0
0
28 Aug 2025
A Feminist Account of Intersectional Algorithmic Fairness
A Feminist Account of Intersectional Algorithmic Fairness
Marie Mirsch
Laila Wegner
Jonas Strube
Carmen Leicht-Scholten
FaML
100
0
0
25 Aug 2025
Applications and Challenges of Fairness APIs in Machine Learning Software
Applications and Challenges of Fairness APIs in Machine Learning SoftwareACM Transactions on Software Engineering and Methodology (TOSEM), 2025
Ajoy Das
Gias Uddin
Shaiful Chowdhury
Mostafijur Rahman Akhond
Hadi Hemmati
FaML
80
0
0
22 Aug 2025
Machine Learning for Medicine Must Be Interpretable, Shareable, Reproducible and Accountable by Design
Machine Learning for Medicine Must Be Interpretable, Shareable, Reproducible and Accountable by Design
Ayyüce Begüm Bektaş
Mithat Gönen
FaMLOOD
100
0
0
22 Aug 2025
Correct-By-Construction: Certified Individual Fairness through Neural Network Training
Correct-By-Construction: Certified Individual Fairness through Neural Network Training
Ruihan Zhang
Jun Sun
FaML
112
0
0
21 Aug 2025
Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing
Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing
Ruicheng Xian
Yuxuan Wan
Han Zhao
FaML
89
0
0
15 Aug 2025
Algorithmic Fairness amid Social Determinants: Reflection, Characterization, and Approach
Algorithmic Fairness amid Social Determinants: Reflection, Characterization, and Approach
Zeyu Tang
Alex John London
Atoosa Kasirzadeh
Sanmi Koyejo
Peter Spirtes
Kun Zhang
FaML
80
0
0
10 Aug 2025
Adversarial Fair Multi-View Clustering
Adversarial Fair Multi-View Clustering
Mudi Jiang
Jiahui Zhou
Lianyu Hu
Xinying Liu
Zengyou He
Zhikui Chen
FaML
96
0
0
06 Aug 2025
Representation biases: will we achieve complete understanding by analyzing representations?
Representation biases: will we achieve complete understanding by analyzing representations?
Andrew Kyle Lampinen
Stephanie Chan
Yuxuan Li
Katherine Hermann
FaML
126
2
0
29 Jul 2025
Algorithmic Fairness: A Runtime Perspective
Algorithmic Fairness: A Runtime PerspectiveRuntime Verification (RV), 2025
Filip Cano
T. Henzinger
Konstantin Kueffner
FaML
131
0
0
28 Jul 2025
Looking for Fairness in Recommender Systems
Looking for Fairness in Recommender Systems
Cécile Logé
FaMLOffRL
51
0
0
16 Jul 2025
Guiding LLM Decision-Making with Fairness Reward Models
Guiding LLM Decision-Making with Fairness Reward Models
Zara Hall
Melanie Subbiah
Thomas P Zollo
Kathleen McKeown
Richard Zemel
FaMLLRM
65
1
0
15 Jul 2025
Fair CCA for Fair Representation Learning: An ADNI Study
Fair CCA for Fair Representation Learning: An ADNI Study
Bojian Hou
Zhanliang Wang
Zhuoping Zhou
Boning Tong
Zexuan Wang
J. Bao
D. Duong-Tran
Q. Long
Li Shen
FaMLOODCML
59
1
0
12 Jul 2025
Monitoring of Static Fairness
Monitoring of Static Fairness
Thomas A. Henzinger
Mahyar Karimi
Konstantin Kueffner
Kaushik Mallik
FaML
58
0
0
03 Jul 2025
Rethinking Algorithmic Fairness for Human-AI Collaboration
Rethinking Algorithmic Fairness for Human-AI Collaboration
Haosen Ge
Hamsa Bastani
Osbert Bastani
FaML
59
1
0
01 Jul 2025
Consumer Beware! Exploring Data Brokers' CCPA Compliance
Consumer Beware! Exploring Data Brokers' CCPA Compliance
Elina van Kempen
Isita Bagayatkar
Pavel Frolikov
Chloe Georgiou
Gene Tsudik
FaMLAILaw
48
1
0
27 Jun 2025
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