PriPrune: Quantifying and Preserving Privacy in Pruned Federated Learning

30 October 2023

Papers citing "PriPrune: Quantifying and Preserving Privacy in Pruned Federated Learning"

3 / 3 papers shown

Title
A Survey on Privacy Risks and Protection in Large Language Models Kang Chen Xiuze Zhou Yuanguo Lin Shibo Feng Li Shen Pengcheng Wu AILaw PILM 112 0 0 04 May 2025
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 57 163 0 29 Sep 2021
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Tianlong Chen Jonathan Frankle Shiyu Chang Sijia Liu Yang Zhang Zhangyang Wang Michael Carbin 148 376 0 23 Jul 2020