An Empirical Analysis of Fairness Notions under Differential Privacy

6 February 2023

Papers citing "An Empirical Analysis of Fairness Notions under Differential Privacy"

9 / 9 papers shown

Title
Fair Play for Individuals, Foul Play for Groups? Auditing Anonymization's Impact on ML Fairness Héber H. Arcolezi Mina Alishahi Adda-Akram Bendoukha Nesrine Kaaniche 36 0 0 12 May 2025
On the Impact of Multi-dimensional Local Differential Privacy on Fairness K. Makhlouf Héber H. Arcolezi Sami Zhioua G. B. Brahim C. Palamidessi 23 5 0 07 Dec 2023
A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defenses Caelin Kaplan Chuan Xu Othmane Marfoq Giovanni Neglia Anderson Santana de Oliveira AAML 52 1 0 18 Oct 2023
Recent Advances of Differential Privacy in Centralized Deep Learning: A Systematic Survey Lea Demelius Roman Kern Andreas Trügler SyDa FedML 32 6 0 28 Sep 2023
Bias Testing and Mitigation in LLM-based Code Generation Dong Huang Qingwen Bu Jie M. Zhang Xiaofei Xie Junjie Chen Heming Cui 45 20 0 03 Sep 2023
(Local) Differential Privacy has NO Disparate Impact on Fairness Héber H. Arcolezi K. Makhlouf C. Palamidessi 40 6 0 25 Apr 2023
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 135 120 0 07 Oct 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 159 350 0 25 Sep 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data Georgi Ganev Bristena Oprisanu Emiliano De Cristofaro 37 57 0 23 Sep 2021