The Skellam Mechanism for Differentially Private Federated Learning
Authors: Naman Agarwal, Peter Kairouz, Ziyu Liu | Published: 2021-10-11 | Updated: 2021-10-29
分散学習
Combining Differential Privacy and Byzantine Resilience in Distributed SGD
Authors: Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Sebastien Rouault, John Stephan | Published: 2021-10-08 | Updated: 2023-10-05
Tolerating Adversarial Attacks and Byzantine Faults in Distributed Machine Learning
Authors: Yusen Wu, Hao Chen, Xin Wang, Chao Liu, Phuong Nguyen, Yelena Yesha | Published: 2021-09-05
An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
Authors: Lunchen Xie, Jiaqi Liu, Songtao Lu, Tsung-hui Chang, Qingjiang Shi | Published: 2021-05-12
Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption
Authors: Jing Ma, Si-Ahmed Naas, Stephan Sigg, Xixiang Lyu | Published: 2021-04-14
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things
Authors: Yansong Gao, Minki Kim, Chandra Thapa, Sharif Abuadbba, Zhi Zhang, Seyit A. Camtepe, Hyoungshick Kim, Surya Nepal | Published: 2021-03-03
Secure Weighted Aggregation for Federated Learning
Authors: Jiale Guo, Ziyao Liu, Kwok-Yan Lam, Jun Zhao, Yiqiang Chen, Chaoping Xing | Published: 2020-10-17 | Updated: 2021-05-11
ByzShield: An Efficient and Robust System for Distributed Training
Authors: Konstantinos Konstantinidis, Aditya Ramamoorthy | Published: 2020-10-10 | Updated: 2021-03-04
Byzantine-Robust Variance-Reduced Federated Learning over Distributed Non-i.i.d. Data
Authors: Jie Peng, Zhaoxian Wu, Qing Ling, Tianyi Chen | Published: 2020-09-17 | Updated: 2021-08-28
FLAME: Differentially Private Federated Learning in the Shuffle Model
Authors: Ruixuan Liu, Yang Cao, Hong Chen, Ruoyang Guo, Masatoshi Yoshikawa | Published: 2020-09-17 | Updated: 2021-03-20