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

Yujun Yan

Joseph E. Gonzalez

Michael W. Mahoney

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

9 / 9 papers shown

Title
Federated Semi-Supervised and Semi-Asynchronous Learning for Anomaly Detection in IoT Networks Wenbin Zhai Feng Wang L. Liu Youwei Ding Wanyi Lu 32 0 0 23 Aug 2023
Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class Imbalance Meirui Jiang Hongzheng Yang Xiaoxiao Li Quande Liu Pheng-Ann Heng Qi Dou FedML 25 23 0 27 Jun 2022
Divergence-aware Federated Self-Supervised Learning Weiming Zhuang Yonggang Wen Shuai Zhang FedML 22 97 0 09 Apr 2022
RSCFed: Random Sampling Consensus Federated Semi-supervised Learning Xiaoxiao Liang Yiqun Lin Huazhu Fu Lei Zhu Xiaomeng Li FedML 19 48 0 26 Mar 2022
Federated Semi-Supervised Learning with Class Distribution Mismatch Zhiguo Wang Xintong Wang Ruoyu Sun Tsung-Hui Chang FedML 14 12 0 29 Oct 2021
Multimodal Federated Learning on IoT Data Yuchen Zhao Payam Barnaghi Hamed Haddadi 13 74 0 10 Sep 2021
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning Zewei Long Jiaqi Wang Yaqing Wang Houping Xiao Fenglong Ma FedML 48 22 0 09 Sep 2021
Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching Quande Liu Hongzhen Yang Qi Dou Pheng-Ann Heng FedML 35 76 0 16 Jun 2021
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems Sixu Hu Yuan N. Li Xu Liu Yue Liu Zhaomin Wu Bingsheng He FedML 18 53 0 14 Jun 2020