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Improving Semi-supervised Federated Learning by Reducing the Gradient
  Diversity of Models

Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models

26 August 2020
Zhengming Zhang
Yaoqing Yang
Z. Yao
Yujun Yan
Joseph E. Gonzalez
Michael W. Mahoney
    FedML
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Papers citing "Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models"

3 / 3 papers shown
Title
Federated Semi-Supervised and Semi-Asynchronous Learning for Anomaly
  Detection in IoT Networks
Federated Semi-Supervised and Semi-Asynchronous Learning for Anomaly Detection in IoT Networks
Wenbin Zhai
Feng Wang
L. Liu
Youwei Ding
Wanyi Lu
20
0
0
23 Aug 2023
Divergence-aware Federated Self-Supervised Learning
Divergence-aware Federated Self-Supervised Learning
Weiming Zhuang
Yonggang Wen
Shuai Zhang
FedML
11
97
0
09 Apr 2022
The OARF Benchmark Suite: Characterization and Implications for
  Federated Learning Systems
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems
Sixu Hu
Yuan N. Li
Xu Liu
Q. Li
Zhaomin Wu
Bingsheng He
FedML
6
53
0
14 Jun 2020
1