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FedCluster: Boosting the Convergence of Federated Learning via
  Cluster-Cycling

FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling

22 September 2020
Cheng Chen
Ziyi Chen
Yi Zhou
B. Kailkhura
    FedML
ArXivPDFHTML

Papers citing "FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling"

13 / 13 papers shown
Title
Is Aggregation the Only Choice? Federated Learning via Layer-wise Model
  Recombination
Is Aggregation the Only Choice? Federated Learning via Layer-wise Model Recombination
Ming Hu
Zhihao Yue
Zhiwei Ling
Cheng Chen
Yihao Huang
Xian Wei
Xiang Lian
Yang Liu
Mingsong Chen
FedML
19
8
0
18 May 2023
CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with
  Clustered Aggregation and Knowledge DIStilled Regularization
CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization
Nang Hung Nguyen
Duc Long Nguyen
Trong Bang Nguyen
T. Nguyen
H. Pham
Truong Thao Nguyen
Phi Le Nguyen
FedML
26
8
0
21 Feb 2023
HiFlash: Communication-Efficient Hierarchical Federated Learning with
  Adaptive Staleness Control and Heterogeneity-aware Client-Edge Association
HiFlash: Communication-Efficient Hierarchical Federated Learning with Adaptive Staleness Control and Heterogeneity-aware Client-Edge Association
Qiong Wu
Xu Chen
Ouyang Tao
Zhi Zhou
Xiaoxi Zhang
Shusen Yang
Junshan Zhang
22
44
0
16 Jan 2023
Fast Adaptive Federated Bilevel Optimization
Fast Adaptive Federated Bilevel Optimization
Feihu Huang
FedML
20
7
0
02 Nov 2022
Edge Learning for B5G Networks with Distributed Signal Processing:
  Semantic Communication, Edge Computing, and Wireless Sensing
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing
Wei Xu
Zhaohui Yang
Derrick Wing Kwan Ng
Marco Levorato
Yonina C. Eldar
Mérouane Debbah
28
398
0
01 Jun 2022
FedCAT: Towards Accurate Federated Learning via Device Concatenation
FedCAT: Towards Accurate Federated Learning via Device Concatenation
Ming Hu
Tian Liu
Zhiwei Ling
Zhihao Yue
Mingsong Chen
FedML
11
1
0
23 Feb 2022
Robust Convergence in Federated Learning through Label-wise Clustering
Robust Convergence in Federated Learning through Label-wise Clustering
Hunmin Lee
Yueyang Liu
Donghyun Kim
Yingshu Li
FedML
19
1
0
28 Dec 2021
Mobility-Aware Cluster Federated Learning in Hierarchical Wireless
  Networks
Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks
Chenyuan Feng
H. Yang
Deshun Hu
Zhiwei Zhao
Tony Q. S. Quek
Geyong Min
28
74
0
20 Aug 2021
Demystifying Why Local Aggregation Helps: Convergence Analysis of
  Hierarchical SGD
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
Jiayi Wang
Shiqiang Wang
Rong-Rong Chen
Mingyue Ji
FedML
28
51
0
24 Oct 2020
Adaptive Personalized Federated Learning
Adaptive Personalized Federated Learning
Yuyang Deng
Mohammad Mahdi Kamani
M. Mahdavi
FedML
206
542
0
30 Mar 2020
Survey of Personalization Techniques for Federated Learning
Survey of Personalization Techniques for Federated Learning
V. Kulkarni
Milind Kulkarni
Aniruddha Pant
FedML
176
326
0
19 Mar 2020
Analyzing Federated Learning through an Adversarial Lens
Analyzing Federated Learning through an Adversarial Lens
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
S. Calo
FedML
179
1,032
0
29 Nov 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
314
11,681
0
09 Mar 2017
1