ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2204.03529
  4. Cited By
FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to
  System Heterogeneity
v1v2 (latest)

FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity

IEEE International Conference on Data Engineering (ICDE), 2022
7 April 2022
Yonghai Gong
Yichuan Li
N. Freris
    FedML
ArXiv (abs)PDFHTML

Papers citing "FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity"

20 / 20 papers shown
Title
Knowledge Adaptation as Posterior Correction
Knowledge Adaptation as Posterior Correction
Mohammad Emtiyaz Khan
157
1
0
17 Jun 2025
Federated ADMM from Bayesian Duality
Federated ADMM from Bayesian Duality
Thomas Möllenhoff
S. Swaroop
Finale Doshi-Velez
Mohammad Emtiyaz Khan
FedML
152
1
0
16 Jun 2025
FedAPM: Federated Learning via ADMM with Partial Model Personalization
Shengkun Zhu
Feiteng Nie
Jinshan Zeng
Sheng Wang
Yuan Sun
Yuan Yao
Shangfeng Chen
Quanqing Xu
Chuanhui Yang
FedML
210
0
0
05 Jun 2025
Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks
Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge NetworksIEEE Transactions on Mobile Computing (IEEE TMC), 2025
Shuai Wang
Yanqing Xu
Chaoqun You
Mingjie Shao
Tony Q.S. Quek
142
2
0
20 Jan 2025
Controlling Participation in Federated Learning with Feedback
Controlling Participation in Federated Learning with FeedbackConference on Learning for Dynamics & Control (L4DC), 2024
Michael Cummins
Güner Dilsad Er
Michael Muehlebach
FedML
333
0
0
28 Nov 2024
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs
A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning NeedsNeural Information Processing Systems (NeurIPS), 2024
Yan Sun
Li Shen
Dacheng Tao
FedML
189
0
0
27 Sep 2024
On ADMM in Heterogeneous Federated Learning: Personalization,
  Robustness, and Fairness
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness
Shengkun Zhu
Jinshan Zeng
Sheng Wang
Yuan Sun
Xiaodong Li
Xingtai Lv
Zhiyong Peng
193
0
0
23 Jul 2024
Distributed Event-Based Learning via ADMM
Distributed Event-Based Learning via ADMM
Güner Dilsad Er
Sebastian Trimpe
Michael Muehlebach
FedML
277
2
0
17 May 2024
SDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks
SDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks
Xin Huang
Weipeng Zhuo
Minh Phu Vuong
Shiju Li
Jongryool Kim
Bradley Rees
Chul-Ho Lee
GNN
202
1
0
02 Apr 2024
On the Convergence of Federated Learning Algorithms without Data
  Similarity
On the Convergence of Federated Learning Algorithms without Data Similarity
Ali Beikmohammadi
Sarit Khirirat
Sindri Magnússon
FedML
228
4
0
29 Feb 2024
FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning
FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning
Yongcun Song
Ziqi Wang
Enrique Zuazua
FedML
201
8
0
21 Feb 2024
Communication-Efficient Heterogeneous Federated Learning with Generalized Heavy-Ball Momentum
Communication-Efficient Heterogeneous Federated Learning with Generalized Heavy-Ball Momentum
Riccardo Zaccone
Sai Praneeth Karimireddy
Carlo Masone
Marco Ciccone
FedML
361
3
0
30 Nov 2023
Personalized Federated Learning via ADMM with Moreau Envelope
Personalized Federated Learning via ADMM with Moreau Envelope
Shengkun Zhu
Jinshan Zeng
Sheng Wang
Yuan Sun
Zhiyong Peng
171
0
0
12 Nov 2023
Federated Learning with Convex Global and Local Constraints
Federated Learning with Convex Global and Local Constraints
Chuan He
Le Peng
Ju Sun
FedML
202
2
0
16 Oct 2023
DFedADMM: Dual Constraints Controlled Model Inconsistency for
  Decentralized Federated Learning
DFedADMM: Dual Constraints Controlled Model Inconsistency for Decentralized Federated Learning
Qinglun Li
Li Shen
Guang-Ming Li
Quanjun Yin
Dacheng Tao
FedML
108
7
0
16 Aug 2023
Understanding How Consistency Works in Federated Learning via Stage-wise
  Relaxed Initialization
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed InitializationNeural Information Processing Systems (NeurIPS), 2023
Yan Sun
Li Shen
Dacheng Tao
FedML
174
19
0
09 Jun 2023
Dynamic Regularized Sharpness Aware Minimization in Federated Learning:
  Approaching Global Consistency and Smooth Landscape
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth LandscapeInternational Conference on Machine Learning (ICML), 2023
Yan Sun
Li Shen
Shi-Yong Chen
Liang Ding
Dacheng Tao
FedML
179
57
0
19 May 2023
Fusion of Global and Local Knowledge for Personalized Federated Learning
Fusion of Global and Local Knowledge for Personalized Federated Learning
Tiansheng Huang
Li Shen
Yan Sun
Weiwei Lin
Dacheng Tao
FedML
159
16
0
21 Feb 2023
FedSpeed: Larger Local Interval, Less Communication Round, and Higher
  Generalization Accuracy
FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization AccuracyInternational Conference on Learning Representations (ICLR), 2023
Yan Sun
Li Shen
Tiansheng Huang
Liang Ding
Dacheng Tao
FedML
171
68
0
21 Feb 2023
Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated
  Learning Framework
Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning FrameworkAAAI Conference on Artificial Intelligence (AAAI), 2022
Shuai Wang
Yanqing Xu
Zihan Wang
Tsung-Hui Chang
Tony Q.S. Quek
Defeng Sun
FedML
180
15
0
03 Dec 2022
1