Stochastic Coded Federated Learning: Theoretical Analysis and Incentive
Mechanism Design

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Stochastic Coded Federated Learning: Theoretical Analysis and Incentive Mechanism Design

IEEE Transactions on Wireless Communications (TWC), 2022

8 November 2022

Jiawei Shao

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Papers citing "Stochastic Coded Federated Learning: Theoretical Analysis and Incentive Mechanism Design"

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Title
Adaptive Coded Federated Learning: Privacy Preservation and Straggler MitigationIEEE Transactions on Communications (IEEE Trans. Commun.), 2024 Chengxi Li Ming Xiao Mikael Skoglund 189 4 0 22 Mar 2024
Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients Xiaolu Wang Zijian Li Shi Jin Jun Zhang FedML 288 6 0 17 Feb 2024
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 238 39 0 20 Jul 2023
MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central UpdatesIEEE Transactions on Mobile Computing (IEEE TMC), 2023 Yuchang Sun Yuyi Mao Jinchao Zhang FedML 235 18 0 21 Jun 2023
Channel and Gradient-Importance Aware Device Scheduling for Over-the-Air Federated LearningIEEE Transactions on Wireless Communications (IEEE TWC), 2023 Yuchang Sun Zehong Lin Yuyi Mao Shi Jin Jinchao Zhang 278 12 0 26 May 2023
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split ModelsIACR Cryptology ePrint Archive (IACR ePrint), 2023 Songze Li Duanyi Yao Jin Liu FedML 279 41 0 26 Apr 2023