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2210.08090
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Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning
14 October 2022
John Nguyen
Jianyu Wang
Kshitiz Malik
Maziar Sanjabi
Michael G. Rabbat
FedML
AI4CE
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Papers citing
"Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning"
16 / 16 papers shown
Title
Capture Global Feature Statistics for One-Shot Federated Learning
Zenghao Guan
Yucan Zhou
Xiaoyan Gu
FedML
68
0
0
10 Mar 2025
Selective Aggregation for Low-Rank Adaptation in Federated Learning
Pengxin Guo
Shuang Zeng
Y. Wang
Huijie Fan
Feifei Wang
Liangqiong Qu
FedML
47
11
0
02 Oct 2024
On the effects of similarity metrics in decentralized deep learning under distributional shift
Edvin Listo Zec
Tom Hagander
Eric Ihre-Thomason
Sarunas Girdzijauskas
FedML
62
0
0
16 Sep 2024
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare
Ming Li
Pengcheng Xu
Junjie Hu
Zeyu Tang
Guang Yang
FedML
48
1
0
15 Sep 2024
FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles
Cyprien Quéméneur
Soumaya Cherkaoui
45
3
0
05 Jun 2024
FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning
Seongyoon Kim
Minchan Jeong
Sungnyun Kim
Sungwoo Cho
Sumyeong Ahn
Se-Young Yun
FedML
50
0
0
04 Jun 2024
FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition
Yuxuan Yan
Qianqian Yang
Shunpu Tang
Zhiguo Shi
38
14
0
29 Apr 2024
Federated Learning over Connected Modes
Dennis Grinwald
Philipp Wiesner
Shinichi Nakajima
FedML
45
0
0
05 Mar 2024
Backdoor Threats from Compromised Foundation Models to Federated Learning
Xi Li
Songhe Wang
Chen Henry Wu
Hao Zhou
Jiaqi Wang
97
10
0
31 Oct 2023
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation
Fu-En Yang
Chien-Yi Wang
Yu-Chiang Frank Wang
VLM
FedML
34
59
0
29 Aug 2023
Federated Model Aggregation via Self-Supervised Priors for Highly Imbalanced Medical Image Classification
Marawan Elbatel
Hualiang Wang
Robert Martí
Huazhu Fu
Xuelong Li
FedML
40
8
0
27 Jul 2023
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
Weiming Zhuang
Chen Chen
Lingjuan Lyu
Chong Chen
Yaochu Jin
Lingjuan Lyu
AIFin
AI4CE
99
86
0
27 Jun 2023
Can Public Large Language Models Help Private Cross-device Federated Learning?
Wei Ping
Yibo Jacky Zhang
Yuan Cao
Bo-wen Li
H. B. McMahan
Sewoong Oh
Zheng Xu
Manzil Zaheer
FedML
29
37
0
20 May 2023
Privately Customizing Prefinetuning to Better Match User Data in Federated Learning
Charlie Hou
Hongyuan Zhan
Akshat Shrivastava
Sida I. Wang
S. Livshits
Giulia Fanti
Daniel Lazar
FedML
32
15
0
17 Feb 2023
When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods
Zhuo Zhang
Yuanhang Yang
Yong Dai
Lizhen Qu
Zenglin Xu
FedML
46
66
0
20 Dec 2022
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
187
412
0
14 Jul 2021
1