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Showing 1 - 20 results of 26 for search '(("distributed coding framework") OR ("distributed computing framework"))', query time: 0.29s Refine Results
  1. 1
    TrustMesh: A Blockchain-Enabled Trusted Distributed Computing Framework for Open Heterogeneous IoT Environments

    TrustMesh: A Blockchain-Enabled Trusted Distributed Computing Framework for Open Heterogeneous IoT Environments by Murtaza Rangwala (20153130)

    Published 2024
    “…These results establish TrustMesh's effectiveness in balancing security, performance, and flexibility requirements in trustless IoT environments, advancing the state-of-the-art in secure distributed computing frameworks.</p>…”
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  2. 2
    Comparison of TodayNew with different intervals under FedAvg, FedProx and SCAFFOLD.

    Comparison of TodayNew with different intervals under FedAvg, FedProx and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  3. 3
    The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.

    The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  4. 4
    Visualization Comparison Between Client Model with NO_EA.

    Visualization Comparison Between Client Model with NO_EA. by Pan Wang (198097)

    Published 2025
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  5. 5
    Comparison of FashionMNIST with different intervals under FedAvg, FedProx and SCAFFOLD.

    Comparison of FashionMNIST with different intervals under FedAvg, FedProx and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  6. 6
    The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.

    The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  7. 7
    Crossover operator.

    Crossover operator. by Pan Wang (198097)

    Published 2025
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  8. 8
    The accuracy of TodayNews dataset under FedAvg, FedProx, and SCAFFOLD.

    The accuracy of TodayNews dataset under FedAvg, FedProx, and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  9. 9
    The accuracy of MNIST dataset under FedAvg, FedProx, and SCAFFOLD.

    The accuracy of MNIST dataset under FedAvg, FedProx, and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  10. 10
    Visualization Comparison Between Client Model with EA.

    Visualization Comparison Between Client Model with EA. by Pan Wang (198097)

    Published 2025
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  11. 11
    Comparison between methods with EA and methods without EA.

    Comparison between methods with EA and methods without EA. by Pan Wang (198097)

    Published 2025
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  12. 12
    Comparison of model distances.

    Comparison of model distances. by Pan Wang (198097)

    Published 2025
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  13. 13
    The process of FL.

    The process of FL. by Pan Wang (198097)

    Published 2025
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  14. 14
    Impact of the Dirichlet distribution.

    Impact of the Dirichlet distribution. by Pan Wang (198097)

    Published 2025
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  15. 15
    Mutation operator.

    Mutation operator. by Pan Wang (198097)

    Published 2025
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  16. 16
    Comparison of MNIST with different intervals under FedAvg, FedProx and SCAFFOLD.

    Comparison of MNIST with different intervals under FedAvg, FedProx and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  17. 17
    Impact of the hyperparameter <i>μ.</i>

    Impact of the hyperparameter <i>μ.</i> by Pan Wang (198097)

    Published 2025
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  18. 18
    The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.

    The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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  19. 19
    Hyper-parameter settings.

    Hyper-parameter settings. by Pan Wang (198097)

    Published 2025
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  20. 20
    The accuracy of MNIST dataset under FedAvg, FedProx, and SCAFFOLD.

    The accuracy of MNIST dataset under FedAvg, FedProx, and SCAFFOLD. by Pan Wang (198097)

    Published 2025
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