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SplitGP: Achieving Both Generalization and Personalization in Federated
  Learning
v1v2 (latest)

SplitGP: Achieving Both Generalization and Personalization in Federated Learning

IEEE Conference on Computer Communications (INFOCOM), 2022
16 December 2022
Dong-Jun Han
Do-Yeon Kim
Minseok Choi
Christopher G. Brinton
Jaekyun Moon
    FedML
ArXiv (abs)PDFHTML

Papers citing "SplitGP: Achieving Both Generalization and Personalization in Federated Learning"

7 / 7 papers shown
Title
Personalized Hierarchical Split Federated Learning in Wireless Networks
Personalized Hierarchical Split Federated Learning in Wireless Networks
Md Ferdous Pervej
Andreas F. Molisch
242
0
0
09 Nov 2024
Fisher Information-based Efficient Curriculum Federated Learning with
  Large Language Models
Fisher Information-based Efficient Curriculum Federated Learning with Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Ji Liu
Jiaxiang Ren
Ruoming Jin
Zijie Zhang
Yang Zhou
P. Valduriez
Dejing Dou
FedML
237
8
0
30 Sep 2024
When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and
  Performance Evaluation
When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation
Chao Huang
Geng Tian
Ming Tang
FedML
202
4
0
23 Aug 2023
Federated Learning for Connected and Automated Vehicles: A Survey of
  Existing Approaches and Challenges
Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and ChallengesIEEE Transactions on Intelligent Vehicles (TIV), 2023
Vishnu Pandi Chellapandi
Liangqi Yuan
Christopher G. Brinton
Stanislaw H. .Zak
Ziran Wang
FedML
334
149
0
21 Aug 2023
Efficient Semi-Supervised Federated Learning for Heterogeneous
  Participants
Efficient Semi-Supervised Federated Learning for Heterogeneous Participants
Zhipeng Sun
Yang Xu
Hong-Ze Xu
Liusheng Huang
C. Qiao
FedML
179
0
0
29 Jul 2023
Communication-Efficient Split Learning via Adaptive Feature-Wise Compression
Communication-Efficient Split Learning via Adaptive Feature-Wise CompressionIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Yong-Nam Oh
Jaeho Lee
Christopher G. Brinton
Yo-Seb Jeon
MQ
289
15
0
20 Jul 2023
PiPar: Pipeline Parallelism for Collaborative Machine Learning
PiPar: Pipeline Parallelism for Collaborative Machine Learning
Zihan Zhang
Philip Rodgers
Peter Kilpatrick
I. Spence
Blesson Varghese
FedML
203
6
0
01 Dec 2022
1