Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2407.00943
Cited By
v1
v2
v3 (latest)
FedEx: Expediting Federated Learning over Heterogeneous Mobile Devices by Overlapping and Participant Selection
1 July 2024
Jiaxiang Geng
Boyu Li
Xiaoqi Qin
Yixuan Li
Liang Li
Yanzhao Hou
Miao Pan
Author Contacts:
lelegjx@bupt.edu.cn
liboyu@bupt.edu.cn
xiaoqiqin@bupt.edu.cn
liyixuan@tyut.edu.cn
lil03@pcl.ac.cn
houyanzhao@bupt.edu.cn
mpan2@uh.edu
FedML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"FedEx: Expediting Federated Learning over Heterogeneous Mobile Devices by Overlapping and Participant Selection"
23 / 23 papers shown
Title
FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction
Samiul Alam
Luyang Liu
Ming Yan
Mi Zhang
160
150
0
03 Dec 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients
Jaemin Shin
Yuanchun Li
Yunxin Liu
Sung-Ju Lee
FedML
55
75
0
05 Jan 2022
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Bing Luo
Wenli Xiao
Shiqiang Wang
Jianwei Huang
Leandros Tassiulas
FedML
84
176
0
21 Dec 2021
Mobile-Former: Bridging MobileNet and Transformer
Yinpeng Chen
Xiyang Dai
Dongdong Chen
Mengchen Liu
Xiaoyi Dong
Lu Yuan
Zicheng Liu
ViT
258
488
0
12 Aug 2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni
Richard Vidal
Laetitia Kameni
Marco Lorenzi
FedML
60
193
0
12 May 2021
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
Su Wang
Mengyuan Lee
Seyyedali Hosseinalipour
Roberto Morabito
M. Chiang
Christopher G. Brinton
FedML
125
112
0
04 Jan 2021
To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices
Liang Li
Dian Shi
Ronghui Hou
Hui Li
Miao Pan
Zhu Han
FedML
62
151
0
22 Dec 2020
Oort: Efficient Federated Learning via Guided Participant Selection
Fan Lai
Xiangfeng Zhu
H. Madhyastha
Mosharaf Chowdhury
FedML
OODD
122
275
0
12 Oct 2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
Enmao Diao
Jie Ding
Vahid Tarokh
FedML
96
558
0
03 Oct 2020
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness
Jinke Ren
Yinghui He
Dingzhu Wen
Guanding Yu
Kaibin Huang
Dongning Guo
88
196
0
01 Apr 2020
Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edge
M. Amiri
Deniz Gunduz
Sanjeev R. Kulkarni
H. Vincent Poor
123
173
0
28 Jan 2020
Federated Learning for Ranking Browser History Suggestions
Florian Hartmann
Sunah Suh
Arkadiusz Komarzewski
Tim Smith
I. Segall
FedML
51
55
0
26 Nov 2019
On the Convergence of FedAvg on Non-IID Data
Xiang Li
Kaixuan Huang
Wenhao Yang
Shusen Wang
Zhihua Zhang
FedML
145
2,334
0
04 Jul 2019
Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent
Shuheng Shen
Linli Xu
Jingchang Liu
Xianfeng Liang
Yifei Cheng
ODL
FedML
46
24
0
28 Jun 2019
Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version)
Guangxu Zhu
Yong Wang
Kaibin Huang
FedML
69
643
0
30 Dec 2018
LEAF: A Benchmark for Federated Settings
S. Caldas
Sai Meher Karthik Duddu
Peter Wu
Tian Li
Jakub Konecný
H. B. McMahan
Virginia Smith
Ameet Talwalkar
FedML
147
1,421
0
03 Dec 2018
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training
Youjie Li
Hang Qiu
Songze Li
A. Avestimehr
Nam Sung Kim
Alex Schwing
FedML
64
104
0
08 Nov 2018
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning
Tianyi Chen
G. Giannakis
Tao Sun
W. Yin
55
298
0
25 May 2018
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
Takayuki Nishio
Ryo Yonetani
FedML
120
1,404
0
23 Apr 2018
TicTac: Accelerating Distributed Deep Learning with Communication Scheduling
Sayed Hadi Hashemi
Sangeetha Abdu Jyothi
R. Campbell
41
197
0
08 Mar 2018
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning
W. Wen
Cong Xu
Feng Yan
Chunpeng Wu
Yandan Wang
Yiran Chen
Hai Helen Li
140
989
0
22 May 2017
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
F. Iandola
Song Han
Matthew W. Moskewicz
Khalid Ashraf
W. Dally
Kurt Keutzer
153
7,486
0
24 Feb 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
406
17,486
0
17 Feb 2016
1