Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2023
DOI: 10.1145/3580305.3599293
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CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning

Gang Yan
1
,
Hao Wang
2
,
Xu Yuan
3
et al.
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Cited by 8 publications
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References 8 publications
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FedPrime: An Adaptive Critical Learning Periods Control Framework for Efficient Federated Learning in Heterogeneity Scenarios

Du,
Yang
2024
Lecture Notes in Computer Science
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FedPrime: An Adaptive Critical Learning Periods Control Framework for Efficient Federated Learning in Heterogeneity Scenarios

Du,
Yang
2024
Lecture Notes in Computer Science
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0
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Auction-based client selection for online Federated Learning

Guo,
Su,
Liu
et al. 2024
Information Fusion
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FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning

Wang,
Wang,
Lyu
et al. 2024
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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