Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems
Authors: Amin Aminifar, Matin Shokri, Amir Aminifar | Published: 2024-05-09 | Updated: 2024-09-13
Communication Efficiency
Boosting Communication Efficiency of Federated Learning’s Secure Aggregation
Authors: Niousha Nazemi, Omid Tavallaie, Shuaijun Chen, Albert Y. Zomaya, Ralph Holz | Published: 2024-05-02
Resilience in Online Federated Learning: Mitigating Model-Poisoning Attacks via Partial Sharing
Authors: Ehsan Lari, Reza Arablouei, Vinay Chakravarthi Gogineni, Stefan Werner | Published: 2024-03-19 | Updated: 2024-08-16
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
Authors: Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi | Published: 2024-03-19
Fluent: Round-efficient Secure Aggregation for Private Federated Learning
Authors: Xincheng Li, Jianting Ning, Geong Sen Poh, Leo Yu Zhang, Xinchun Yin, Tianwei Zhang | Published: 2024-03-10
OPAF: Optimized Secure Two-Party Computation Protocols for Nonlinear Activation Functions in Recurrent Neural Network
Authors: Qian Feng, Zhihua Xia, Zhifeng Xu, Jiasi Weng, Jian Weng | Published: 2024-03-01
Privacy-preserving quantum federated learning via gradient hiding
Authors: Changhao Li, Niraj Kumar, Zhixin Song, Shouvanik Chakrabarti, Marco Pistoia | Published: 2023-12-07
Bicoptor: Two-round Secure Three-party Non-linear Computation without Preprocessing for Privacy-preserving Machine Learning
Authors: Lijing Zhou, Ziyu Wang, Hongrui Cui, Qingrui Song, Yu Yu | Published: 2022-10-05 | Updated: 2024-04-19
Joint Privacy Enhancement and Quantization in Federated Learning
Authors: Natalie Lang, Elad Sofer, Tomer Shaked, Nir Shlezinger | Published: 2022-08-23
Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy
Authors: Wenqiang Ruan, Mingxin Xu, Wenjing Fang, Li Wang, Lei Wang, Weili Han | Published: 2022-08-18