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A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models.

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Federated Deep Learning with Bayesian Privacy., , , , , and . CoRR, (2021)Evaluating Membership Inference Attacks and Defenses in Federated Learning., , , , , , and . CoRR, (2024)FedPDD: A Privacy-preserving Double Distillation Framework for Cross-silo Federated Recommendation., , , and . IJCNN, page 1-8. IEEE, (2023)No Free Lunch Theorem for Security and Utility in Federated Learning., , , , and . ACM Trans. Intell. Syst. Technol., 14 (1): 1:1-1:35 (February 2023)FedIPR: Ownership Verification for Federated Deep Neural Network Models., , , , and . CoRR, (2021)Optimizing Privacy, Utility and Efficiency in Constrained Multi-Objective Federated Learning., , , , , , , , , and . CoRR, (2023)Temporal Gradient Inversion Attacks with Robust Optimization., , , , , , , and . CoRR, (2023)FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof., , , , , , and . CoRR, (2023)FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model., , , , , , , and . CoRR, (2022)A Theoretical Analysis of Efficiency Constrained Utility-Privacy Bi-Objective Optimization in Federated Learning., , , , , and . CoRR, (2023)