FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the
Power of Heterogeneous Clients

FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients

19 November 2023

Papers citing "FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients"

9 / 9 papers shown

Title
A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning Jieming Bian Yuanzhe Peng Lei Wang Yin Huang Jie Xu FedML 55 0 0 29 Apr 2025
FedSCA: Federated Tuning with Similarity-guided Collaborative Aggregation for Heterogeneous Medical Image Segmentation Yumin Zhang Yan Gao Haoran Duan Hanqing Guo Tejal Shah R. Ranjan Bo Wei FedML 68 0 0 19 Mar 2025
A Survey on Federated Fine-tuning of Large Language Models Yebo Wu Chunlin Tian Jingguang Li He Sun Kahou Tam Li Li Chengzhong Xu FedML 81 0 0 15 Mar 2025
PEFT-as-an-Attack! Jailbreaking Language Models during Federated Parameter-Efficient Fine-Tuning Shenghui Li Edith C. H. Ngai Fanghua Ye Thiemo Voigt SILM 83 3 0 28 Nov 2024
Fed-piLot: Optimizing LoRA Assignment for Efficient Federated Foundation Model Fine-Tuning Zikai Zhang Jiahao Xu Ping Liu Rui Hu 22 2 0 14 Oct 2024
Synergizing Foundation Models and Federated Learning: A Survey Shenghui Li Fanghua Ye Meng Fang Jiaxu Zhao Yun-Hin Chan Edith C. -H. Ngai Thiemo Voigt AI4CE 43 5 0 18 Jun 2024
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 239 2,554 0 04 May 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 165 267 0 26 Feb 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 770 0 15 Feb 2021