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Efficient Asynchronous Federated Learning with Sparsification and
  Quantization

Efficient Asynchronous Federated Learning with Sparsification and Quantization

23 December 2023
Juncheng Jia
Ji Liu
Chendi Zhou
Hao Tian
M. Dong
Dejing Dou
    FedML
ArXivPDFHTML

Papers citing "Efficient Asynchronous Federated Learning with Sparsification and Quantization"

9 / 9 papers shown
Title
Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data Sources
Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data Sources
Siddhant Dutta
Iago Leal de Freitas
Pedro Maciel Xavier
Claudio Miceli de Farias
David E. Bernal Neira
AI4CE
FedML
71
0
0
23 Nov 2024
Trustworthy Federated Learning: Privacy, Security, and Beyond
Trustworthy Federated Learning: Privacy, Security, and Beyond
Chunlu Chen
Ji Liu
Haowen Tan
Xingjian Li
Kevin I-Kai Wang
Peng Li
Kouichi Sakurai
Dejing Dou
FedML
47
3
0
03 Nov 2024
Fisher Information-based Efficient Curriculum Federated Learning with
  Large Language Models
Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models
Ji Liu
Jiaxiang Ren
Ruoming Jin
Zijie Zhang
Yang Zhou
P. Valduriez
Dejing Dou
FedML
19
1
0
30 Sep 2024
Efficient Federated Learning Using Dynamic Update and Adaptive Pruning
  with Momentum on Shared Server Data
Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data
Ji Liu
Juncheng Jia
Hong Zhang
Yuhui Yun
Leye Wang
Yang Zhou
H. Dai
Dejing Dou
FedML
21
5
0
11 Aug 2024
Enhancing Trust and Privacy in Distributed Networks: A Comprehensive
  Survey on Blockchain-based Federated Learning
Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning
Ji Liu
Chunlu Chen
Yu Li
Lin Sun
Yulun Song
Jingbo Zhou
Bo Jing
Dejing Dou
31
9
0
28 Mar 2024
AEDFL: Efficient Asynchronous Decentralized Federated Learning with
  Heterogeneous Devices
AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices
Ji Liu
Tianshi Che
Yang Zhou
Ruoming Jin
H. Dai
Dejing Dou
P. Valduriez
23
12
0
18 Dec 2023
FedASMU: Efficient Asynchronous Federated Learning with Dynamic
  Staleness-aware Model Update
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-aware Model Update
Ji Liu
Juncheng Jia
Tianshi Che
Chao Huo
Jiaxiang Ren
Yang Zhou
H. Dai
Dejing Dou
11
30
0
10 Dec 2023
Asynchronous Federated Learning on Heterogeneous Devices: A Survey
Asynchronous Federated Learning on Heterogeneous Devices: A Survey
Chenhao Xu
Youyang Qu
Yong Xiang
Longxiang Gao
FedML
89
237
0
09 Sep 2021
Adaptive Federated Learning in Resource Constrained Edge Computing
  Systems
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
K. Leung
C. Makaya
T. He
Kevin S. Chan
141
1,680
0
14 Apr 2018
1