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Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients

Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients

Xiaolu Wang
Zijian Li
Shi Jin
Jun Zhang
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Papers citing "Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients"

4 / 4 papers shown
Title
Convergence Analysis of Asynchronous Federated Learning with Gradient Compression for Non-Convex Optimization
Convergence Analysis of Asynchronous Federated Learning with Gradient Compression for Non-Convex Optimization
Diying Yang
Yingwei Hou
Danyang Xiao
Weigang Wu
FedML
39
0
0
28 Apr 2025
FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices
FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices
Dezhong Yao
Yuexin Shi
Tongtong Liu
Zhiqiang Xu
69
1
0
12 Feb 2025
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
Dual-Delayed Asynchronous SGD for Arbitrarily Heterogeneous Data
Xiaolu Wang
Yuchang Sun
Hoi-To Wai
Jun Zhang
49
0
0
27 May 2024
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing
Jiawei Shao
Yuchang Sun
Songze Li
Jun Zhang
OOD
27
37
0
06 Oct 2022