Towards Utilizing Unlabeled Data in Federated Learning: A Survey and
Prospective

Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective

26 February 2020

Yang Liu

Papers citing "Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective"

8 / 8 papers shown

Title
Federated Unsupervised Domain Generalization using Global and Local Alignment of Gradients Farhad Pourpanah Mahdiyar Molahasani Milad Soltany Michael A. Greenspan Ali Etemad FedML OOD 81 2 0 25 May 2024
FedIL: Federated Incremental Learning from Decentralized Unlabeled Data with Convergence Analysis Nan Yang Dong Yuan Charles Z. Liu Yong Deng Wei Bao FedML 58 5 0 23 Feb 2023
Divergence-aware Federated Self-Supervised Learning Weiming Zhuang Yonggang Wen Shuai Zhang FedML 22 97 0 09 Apr 2022
TinyMLOps: Operational Challenges for Widespread Edge AI Adoption Sam Leroux Pieter Simoens Meelis Lootus Kartik Thakore Akshay Sharma 19 16 0 21 Mar 2022
Privacy-preserving Speech Emotion Recognition through Semi-Supervised Federated Learning Vasileios Tsouvalas T. Ozcelebi N. Meratnia 26 21 0 05 Feb 2022
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning Zewei Long Jiaqi Wang Yaqing Wang Houping Xiao Fenglong Ma FedML 40 22 0 09 Sep 2021
Federated Unsupervised Representation Learning Fengda Zhang Kun Kuang Zhaoyang You T. Shen Jun Xiao Yin Zhang Chao-Xiang Wu Yueting Zhuang Xiaolin Li FedML 20 133 0 18 Oct 2020
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 261 1,275 0 06 Mar 2017