Training individually fair ML models with Sensitive Subspace Robustness

28 June 2019

Papers citing "Training individually fair ML models with Sensitive Subspace Robustness"

26 / 26 papers shown

Title
Local Statistical Parity for the Estimation of Fair Decision Trees Andrea Quintanilla Johan Van Horebeek 37 0 0 25 Apr 2025
CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models Song Wang Peng Wang Tong Zhou Yushun Dong Zhen Tan Jundong Li CoGe 53 7 0 02 Jul 2024
Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects Conrad Sanderson David M. Douglas Qinghua Lu 37 11 0 17 Apr 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 12 13 0 06 Mar 2023
Identifying, measuring, and mitigating individual unfairness for supervised learning models and application to credit risk models Rasoul Shahsavarifar Jithu Chandran M. Inchiosa A. Deshpande Mario Schlener V. Gossain Yara Elias Vinaya Murali FaML 16 0 0 11 Nov 2022
InfoOT: Information Maximizing Optimal Transport Ching-Yao Chuang Stefanie Jegelka David Alvarez-Melis OT 35 12 0 06 Oct 2022
iFlipper: Label Flipping for Individual Fairness Hantian Zhang Ki Hyun Tae Jaeyoung Park Xu Chu Steven Euijong Whang 33 6 0 15 Sep 2022
RMExplorer: A Visual Analytics Approach to Explore the Performance and the Fairness of Disease Risk Models on Population Subgroups Bum Chul Kwon U. Kartoun S. Khurshid Mikhail Yurochkin Subha Maity Deanna G. Brockman A. Khera P. Ellinor S. Lubitz Kenney Ng 28 11 0 14 Sep 2022
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networks Kiarash Mohammadi Aishwarya Sivaraman G. Farnadi 17 5 0 01 Jun 2022
CertiFair: A Framework for Certified Global Fairness of Neural Networks Haitham Khedr Yasser Shoukry FedML 23 19 0 20 May 2022
Accurate Fairness: Improving Individual Fairness without Trading Accuracy Xuran Li Peng Wu Jing Su FaML 33 17 0 18 May 2022
De-biasing "bias" measurement K. Lum Yunfeng Zhang Amanda Bower 15 26 0 11 May 2022
Individual Fairness Guarantees for Neural Networks Elias Benussi A. Patané Matthew Wicker Luca Laurenti Marta Kwiatkowska University of Oxford 20 21 0 11 May 2022
Optimising Equal Opportunity Fairness in Model Training Aili Shen Xudong Han Trevor Cohn Timothy Baldwin Lea Frermann FaML 29 28 0 05 May 2022
SLIDE: a surrogate fairness constraint to ensure fairness consistency Kunwoong Kim Ilsang Ohn Sara Kim Yongdai Kim 29 4 0 07 Feb 2022
Latent Space Smoothing for Individually Fair Representations Momchil Peychev Anian Ruoss Mislav Balunović Maximilian Baader Martin Vechev FaML 36 19 0 26 Nov 2021
A Fairness Analysis on Private Aggregation of Teacher Ensembles Cuong Tran M. H. Dinh Kyle Beiter Ferdinando Fioretto 21 12 0 17 Sep 2021
Fair Mixup: Fairness via Interpolation Ching-Yao Chuang Youssef Mroueh 21 137 0 11 Mar 2021
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 23 61 0 18 Jul 2020
Two Simple Ways to Learn Individual Fairness Metrics from Data Debarghya Mukherjee Mikhail Yurochkin Moulinath Banerjee Yuekai Sun FaML 26 96 0 19 Jun 2020
Auditing ML Models for Individual Bias and Unfairness Songkai Xue Mikhail Yurochkin Yuekai Sun MLAU 40 22 0 11 Mar 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 15 92 0 24 Feb 2020
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 674 0 17 Feb 2018
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,082 0 24 Oct 2016