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FedDCT: Federated Learning of Large Convolutional Neural Networks on
  Resource Constrained Devices using Divide and Collaborative Training

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Collaborative Training

20 November 2022
Quan Nguyen
Hieu H. Pham
Kok-Seng Wong
Phi Le Nguyen
Truong Thao Nguyen
Minh N. Do
    FedML
ArXivPDFHTML

Papers citing "FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Collaborative Training"

4 / 4 papers shown
Title
Beyond Model Scale Limits: End-Edge-Cloud Federated Learning with Self-Rectified Knowledge Agglomeration
Zhiyuan Wu
Sheng Sun
Yuwei Wang
Min Liu
Ke Xu
Quyang Pan
Bo Gao
Tian Wen
FedML
30
0
0
03 Jan 2025
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity
  with KARMA
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA
M. Wahib
Haoyu Zhang
Truong Thao Nguyen
Aleksandr Drozd
Jens Domke
Lingqi Zhang
Ryousei Takano
Satoshi Matsuoka
OODD
32
23
0
26 Aug 2020
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
297
10,216
0
16 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
PINN
3DV
249
36,362
0
25 Aug 2016
1