Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging

24 July 2023

Papers citing "Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging"

8 / 8 papers shown

Title
FedPCA: Noise-Robust Fair Federated Learning via Performance-Capacity Analysis Nannan Wu Zengqiang Yan Nong Sang Li Yu Chang Wen Chen 43 0 0 13 Mar 2025
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering He Zhu Ren Togo Takahiro Ogawa Miki Haseyama MedIm 31 0 0 23 Oct 2024
Enable the Right to be Forgotten with Federated Client Unlearning in Medical Imaging Zhipeng Deng Luyang Luo Hao Chen MU 37 2 0 02 Jul 2024
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 168 350 0 25 Sep 2021
Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication Muah Kim Onur Gunlu Rafael F. Schaefer FedML 110 118 0 09 Feb 2021
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 147 178 0 28 Jul 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,707 0 18 Mar 2020
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 309 36,371 0 25 Aug 2016