Two Simple Ways to Learn Individual Fairness Metrics from Data

19 June 2020

Papers citing "Two Simple Ways to Learn Individual Fairness Metrics from Data"

50 / 56 papers shown

Title
Testing Individual Fairness in Graph Neural Networks Roya Nasiri 22 0 0 25 Apr 2025
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction Siqi Li Qiming Wu Xin Li Di Miao Chuan Hong ... Michael Hao Chen Mengying Yan Yilin Ning M. Ong Nan Liu 26 1 0 07 Oct 2024
Positive-Sum Fairness: Leveraging Demographic Attributes to Achieve Fair AI Outcomes Without Sacrificing Group Gains Samia Belhadj Sanguk Park Ambika Seth Hesham Dar Thijs Kooi 19 1 0 30 Sep 2024
Rethinking Fair Graph Neural Networks from Re-balancing Zhixun Li Yushun Dong Qiang Liu Jeffrey Xu Yu 21 7 0 16 Jul 2024
AIM: Attributing, Interpreting, Mitigating Data Unfairness Zhining Liu Ruizhong Qiu Zhichen Zeng Yada Zhu Hendrik Hamann Hanghang Tong FaML 29 4 0 13 Jun 2024
Individual Fairness Through Reweighting and Tuning A. J. Mahamadou Lea Goetz Russ B. Altman 28 0 0 02 May 2024
Monotone Individual Fairness Yahav Bechavod 23 2 0 11 Mar 2024
Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning Hidde Lycklama Alexander Viand Nicolas Küchler Christian Knabenhans Anwar Hithnawi 44 6 0 24 Feb 2024
On the Impact of Output Perturbation on Fairness in Binary Linear Classification Vitalii Emelianov Michael Perrot FaML 27 0 0 05 Feb 2024
Uncertainty-based Fairness Measures Selim Kuzucu Jiaee Cheong Hatice Gunes Sinan Kalkan UD PER 37 4 0 18 Dec 2023
Democratize with Care: The need for fairness specific features in user-interface based open source AutoML tools Sundaraparipurnan Narayanan 20 0 0 16 Dec 2023
Certification of Distributional Individual Fairness Matthew Wicker Vihari Piratla Adrian Weller 19 1 0 20 Nov 2023
Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness A. Ehyaei G. Farnadi Samira Samadi 15 1 0 30 Oct 2023
Identifying Reasons for Bias: An Argumentation-Based Approach Madeleine Waller Odinaldo Rodrigues O. Cocarascu FaML 20 1 0 25 Oct 2023
A Canonical Data Transformation for Achieving Inter- and Within-group Fairness Zachary McBride Lazri Ivan Brugere Xin Tian Dana Dachman-Soled Antigoni Polychroniadou Danial Dervovic Min Wu 13 0 0 23 Oct 2023
Software Doping Analysis for Human Oversight Sebastian Biewer Kevin Baum Sarah Sterz Holger Hermanns Sven Hetmank Markus Langer Anne Lauber-Rönsberg Franz Lehr 14 4 0 11 Aug 2023
The Flawed Foundations of Fair Machine Learning R. Poe Soumia Zohra El Mestari FaML 17 1 0 02 Jun 2023
Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness Evaluation Yifei Wang Zhengyang Zhou Liqin Wang John Laurentiev Peter Hou Li Zhou Pengyu Hong 19 0 0 29 May 2023
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint Paiheng Xu Yuhang Zhou Bang An Wei Ai Furong Huang 20 6 0 25 May 2023
To be Robust and to be Fair: Aligning Fairness with Robustness Junyi Chai Xiaoqian Wang 23 2 0 31 Mar 2023
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
Achieving Counterfactual Fairness with Imperfect Structural Causal Model Tri Dung Duong Qian Li Guandong Xu 14 2 0 26 Mar 2023
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach Zhimeng Jiang Xiaotian Han Hongye Jin Guanchu Wang Rui Chen Na Zou Xia Hu 8 13 0 06 Mar 2023
Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness Zahra Ashktorab Benjamin Hoover Mayank Agarwal Casey Dugan Werner Geyer Han Yang Mikhail Yurochkin FaML 23 17 0 01 Mar 2023
Individual Fairness under Uncertainty Wenbin Zhang Zichong Wang Juyong Kim Cheng Cheng Thomas Oommen Pradeep Ravikumar Jeremy C. Weiss FaML 29 12 0 16 Feb 2023
Retiring $Δ$ DP: New Distribution-Level Metrics for Demographic Parity Xiaotian Han Zhimeng Jiang Hongye Jin Zirui Liu Na Zou Qifan Wang Xia Hu 27 3 0 31 Jan 2023
Human-Guided Fair Classification for Natural Language Processing Florian E.Dorner Momchil Peychev Nikola Konstantinov Naman Goel Elliott Ash Martin Vechev FaML 11 3 0 20 Dec 2022
Manifestations of Xenophobia in AI Systems Nenad Tomašev J. L. Maynard Iason Gabriel 24 9 0 15 Dec 2022
Learning Antidote Data to Individual Unfairness Peizhao Li Ethan Xia Hongfu Liu FedML FaML 9 9 0 29 Nov 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 11 14 0 27 Oct 2022
VerifyML: Obliviously Checking Model Fairness Resilient to Malicious Model Holder Guowen Xu Xingshuo Han Gelei Deng Tianwei Zhang Shengmin Xu Jianting Ning Anjia Yang Hongwei Li 15 4 0 16 Oct 2022
fAux: Testing Individual Fairness via Gradient Alignment Giuseppe Castiglione Ga Wu C. Srinivasa Simon J. D. Prince 11 3 0 10 Oct 2022
iFlipper: Label Flipping for Individual Fairness Hantian Zhang Ki Hyun Tae Jaeyoung Park Xu Chu Steven Euijong Whang 25 6 0 15 Sep 2022
Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions Leonidas Tsepenekas Ivan Brugere Freddy Lecue Daniele Magazzeni 16 1 0 26 Aug 2022
Individually Fair Learning with One-Sided Feedback Yahav Bechavod Aaron Roth FaML 14 3 0 09 Jun 2022
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective Zeyu Tang Jiji Zhang Kun Zhang FaML 17 26 0 08 Jun 2022
Multi-disciplinary fairness considerations in machine learning for clinical trials Isabel Chien Nina Deliu Richard E. Turner Adrian Weller S. Villar Niki Kilbertus FaML 29 20 0 18 May 2022
Individual Fairness Guarantees for Neural Networks Elias Benussi A. Patané Matthew Wicker Luca Laurenti Marta Kwiatkowska University of Oxford 15 21 0 11 May 2022
Domain Adaptation meets Individual Fairness. And they get along Debarghya Mukherjee Felix Petersen Mikhail Yurochkin Yuekai Sun FaML 14 16 0 01 May 2022
SLIDE: a surrogate fairness constraint to ensure fairness consistency Kunwoong Kim Ilsang Ohn Sara Kim Yongdai Kim 19 4 0 07 Feb 2022
Learning fair representation with a parametric integral probability metric Dongha Kim Kunwoong Kim Insung Kong Ilsang Ohn Yongdai Kim FaML 17 16 0 07 Feb 2022
Latent Space Smoothing for Individually Fair Representations Momchil Peychev Anian Ruoss Mislav Balunović Maximilian Baader Martin Vechev FaML 28 18 0 26 Nov 2021
Unified Group Fairness on Federated Learning Fengda Zhang Kun Kuang Yuxuan Liu Long Chen Chao-Xiang Wu Fei Wu Jiaxun Lu Yunfeng Shao Jun Xiao FedML 49 20 0 09 Nov 2021
Post-processing for Individual Fairness Felix Petersen Debarghya Mukherjee Yuekai Sun Mikhail Yurochkin FaML 9 80 0 26 Oct 2021
A Sociotechnical View of Algorithmic Fairness Mateusz Dolata Stefan Feuerriegel Gerhard Schwabe FaML 17 92 0 27 Sep 2021
Individually Fair Gradient Boosting Alexander Vargo Fan Zhang Mikhail Yurochkin Yuekai Sun FaML FedML 11 15 0 31 Mar 2021
Statistical inference for individual fairness Subha Maity Songkai Xue Mikhail Yurochkin Yuekai Sun FaML 17 20 0 30 Mar 2021
Individually Fair Ranking Amanda Bower Hamid Eftekhari Mikhail Yurochkin Yuekai Sun FaML 13 11 0 19 Mar 2021
Quadratic Metric Elicitation for Fairness and Beyond G. Hiranandani Jatin Mathur Harikrishna Narasimhan Oluwasanmi Koyejo 17 5 0 03 Nov 2020
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness Mikhail Yurochkin Yuekai Sun FaML 9 49 0 25 Jun 2020