71 citations · 71 across the 1 of their papers we have counts for
3 papers
cs.LG2020
Federated Unsupervised Representation Learning
Fengda Zhang, Kun Kuang, Zhaoyang You +6
To leverage enormous unlabeled data on distributed edge devices, we formulate a new problem in federated learning called Federated Unsupervised Representation Learning (FURL) to le…
cs.LG2020★ 71 cited
Federated Mutual Learning
Tao Shen, Jie Zhang, Xinkang Jia +6
Federated learning (FL) enables collaboratively training deep learning models on decentralized data. However, there are three types of heterogeneities in FL setting bringing about…
cs.LG2020
Evaluation Framework For Large-scale Federated Learning
Lifeng Liu, Fengda Zhang, Jun Xiao +1
Federated learning is proposed as a machine learning setting to enable distributed edge devices, such as mobile phones, to collaboratively learn a shared prediction model while kee…