Differentially Private Post-Processing for Fair Regression
Authors: Ruicheng Xian, Qiaobo Li, Gautam Kamath, Han Zhao | Published: 2024-05-07
公平性評価
Privacy at a Price: Exploring its Dual Impact on AI Fairness
Authors: Mengmeng Yang, Ming Ding, Youyang Qu, Wei Ni, David Smith, Thierry Rakotoarivelo | Published: 2024-04-15
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy
Authors: Songjie Xie, Youlong Wu, Jiaxuan Li, Ming Ding, Khaled B. Letaief | Published: 2024-02-16
Position Paper: Assessing Robustness, Privacy, and Fairness in Federated Learning Integrated with Foundation Models
Authors: Xi Li, Jiaqi Wang | Published: 2024-02-02
In the Name of Fairness: Assessing the Bias in Clinical Record De-identification
Authors: Yuxin Xiao, Shulammite Lim, Tom Joseph Pollard, Marzyeh Ghassemi | Published: 2023-05-18 | Updated: 2024-01-03
(Local) Differential Privacy has NO Disparate Impact on Fairness
Authors: Héber H. Arcolezi, Karima Makhlouf, Catuscia Palamidessi | Published: 2023-04-25 | Updated: 2023-08-01
PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning
Authors: Sikha Pentyala, Nicola Neophytou, Anderson Nascimento, Martine De Cock, Golnoosh Farnadi | Published: 2022-05-23 | Updated: 2022-08-26
Statistical inference for individual fairness
Authors: Subha Maity, Songkai Xue, Mikhail Yurochkin, Yuekai Sun | Published: 2021-03-30
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning
Authors: Pieter Delobelle, Paul Temple, Gilles Perrouin, Benoît Frénay, Patrick Heymans, Bettina Berendt | Published: 2020-05-14 | Updated: 2020-09-01