Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy

26 September 2022

Papers citing "Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy"

8 / 8 papers shown

Title
FedMABench: Benchmarking Mobile Agents on Decentralized Heterogeneous User Data Wenhao Wang Zijie Yu Rui Ye J. Zhang S. Chen Yanfeng Wang FedML 48 0 0 07 Mar 2025
On Lattices, Learning with Errors, Random Linear Codes, and Cryptography O. Regev LRM 69 1,072 0 08 Jan 2024
Lotto: Secure Participant Selection against Adversarial Servers in Federated Learning Zhifeng Jiang Peng Ye Shiqi He Wei Wang Ruichuan Chen Bo Li 23 2 0 05 Jan 2024
LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning Jinhyun So Chaoyang He Chien-Sheng Yang Songze Li Qian-long Yu Ramy E. Ali Başak Güler Salman Avestimehr FedML 64 164 0 29 Sep 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 184 411 0 14 Jul 2021
Practical and Private (Deep) Learning without Sampling or Shuffling Peter Kairouz Brendan McMahan Shuang Song Om Thakkar Abhradeep Thakurta Zheng Xu FedML 182 154 0 26 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications Matthias Paulik M. Seigel Henry Mason Dominic Telaar Joris Kluivers ... Dominic Hughes O. Javidbakht Fei Dong Rehan Rishi Stanley Hung FedML 177 126 0 16 Feb 2021
IBM Federated Learning: an Enterprise Framework White Paper V0.1 Heiko Ludwig Nathalie Baracaldo Gegi Thomas Yi Zhou Ali Anwar ... Sean Laguna Mikhail Yurochkin Mayank Agarwal Ebube Chuba Annie Abay FedML 128 157 0 22 Jul 2020