CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization-Reference-Cited by-同舟云学术

CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization

Published:2023-05 Issue: Volume: Page:
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Container-title:2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
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Author:

Nguyen Nang Hung¹,Nguyen Duc Long¹,Nguyen Trong Bang¹,Nguyen Thanh-Hung¹,Pham Huy Hieu²,Nguyen Truong Thao³,Nguyen Phi Le¹

Affiliation:

1. School of Information and Communication Technology, Hanoi University of Science and Technology,Hanoi,Vietnam

2. College of Engineering & Computer Science and VinUni-Illinois Smart Health Center, VinUniversity

3. The National Institute of Advanced Industrial Science and Technology (AIST),Japan

Publisher

IEEE

Link

Reference53 articles.

1. On the convergence of FedAvg on Non-IID data;li;8th International Conference on Learning Representations ICLR 2020,2020

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1. Hierarchical Federated Learning in MEC Networks with Knowledge Distillation;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30