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Secure and Efficient Decentralized Federated Learning with Data Representation Protection.

, , , and . CoRR, (2022)

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Convergence of Edge Computing and Deep Learning: A Comprehensive Survey., , , , , and . CoRR, (2019)Vision, application scenarios, and key technology trends for 6G mobile communications., , , , , , , , , and 11 other author(s). Sci. China Inf. Sci., 65 (5): 1-27 (2022)Componentized Task Scheduling in Cloud-Edge Cooperative Scenarios Based on GNN-enhanced DRL., , , , , , and . NOMS, page 1-4. IEEE, (2023)Edge AI - Convergence of Edge Computing and Artificial Intelligence, , , , , and . Springer, (2020)Task Decomposition of Network Services for Deploying in Heterogeneous Network Computing Nodes., , , , , , , and . CAMAD, page 1-6. IEEE, (2021)The Confluence of Blockchain and 6G Network: Scenarios Analysis and Performance Assessment., , , and . CoRR, (2022)Advancing Federated Learning in 6G: A Trusted Architecture with Graph-Based Analysis., , , , and . GLOBECOM, page 56-61. IEEE, (2023)A Blockchain-based Subscriber Data Management Scheme for 6G Mobile Communication System., , , , and . GLOBECOM (Workshops), page 1-6. IEEE, (2021)FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity., , , and . KDD, page 1954-1964. ACM, (2023)Knowledge Graph Completion by Multi-Channel Translating Embeddings., , , , , , , , and . ICTAI, page 361-365. IEEE, (2022)