Federated learning from only unlabeled data with class-conditional-sharing clients

N Lu, Z Wang, X Li, G Niu, Q Dou… - arXiv preprint arXiv …, 2022 - arxiv.org
Supervised federated learning (FL) enables multiple clients to share the trained model
without sharing their labeled data. However, potential clients might even be reluctant to label …
被引用次数：41 相关文章

Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients

N Lu, Z Wang, X Li, G Niu, Q Dou… - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Supervised federated learning (FL) enables multiple clients to share the trained model
without sharing their labeled data. However, potential clients might even be reluctant to label …
[PDF] github.io

[PDF][PDF] FEDERATED LEARNING FROM ONLY UNLABELED DATA WITH CLASS-CONDITIONAL-SHARING CLIENTS

N Lu, Z Wang, X Li, G Niu, Q Dou, M Sugiyama - niug1984.github.io
Supervised federated learning (FL) enables multiple clients to share the trained model
without sharing their labeled data. However, potential clients might even be reluctant to label …

Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients

N Lu, Z Wang, X Li, G Niu, Q Dou… - … Conference on Learning …, 2021 - openreview.net
Supervised federated learning (FL) enables multiple clients to share the trained model
without sharing their labeled data. However, potential clients might even be reluctant to label …
[PDF] openreview.net

[PDF][PDF] FEDERATED LEARNING FROM ONLY UNLABELED DATA WITH CLASS-CONDITIONAL-SHARING CLIENTS

N Lu, Z Wang, X Li, G Niu, Q Dou, M Sugiyama - openreview.net
Supervised federated learning (FL) enables multiple clients to share the trained model
without sharing their labeled data. However, potential clients might even be reluctant to label …