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Accelerating Federated Learning by Selecting Beneficial Herd of Local
  Gradients

Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients

25 March 2024
Ping Luo
Xiaoge Deng
Ziqing Wen
Tao Sun
Dongsheng Li
    FedML
ArXivPDFHTML

Papers citing "Accelerating Federated Learning by Selecting Beneficial Herd of Local Gradients"

4 / 4 papers shown
Title
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
Ziheng Qin
K. Wang
Zangwei Zheng
Jianyang Gu
Xiang Peng
...
Daquan Zhou
Lei Shang
Baigui Sun
Xuansong Xie
Yang You
116
46
0
08 Mar 2023
Dataset Pruning: Reducing Training Data by Examining Generalization
  Influence
Dataset Pruning: Reducing Training Data by Examining Generalization Influence
Shuo Yang
Zeke Xie
Hanyu Peng
Minjing Xu
Mingming Sun
P. Li
DD
144
106
0
19 May 2022
Adaptive Federated Learning in Resource Constrained Edge Computing
  Systems
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
K. Leung
C. Makaya
T. He
Kevin S. Chan
144
1,680
0
14 Apr 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
243
11,659
0
09 Mar 2017
1