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Meeting Users' QoS in a Edge-to-Cloud Platform via Optimally Placing Services and Scheduling Tasks., and . ICNC, page 368-372. IEEE, (2020)Wrapper-Based Federated Feature Selection for IoT Environments., and . ICNC, page 214-219. IEEE, (2023)A Framework for Edge Intelligent Smart Distribution Grids via Federated Learning., , , , , and . ICCCN, page 1-9. IEEE, (2021)Resource-aware Federated Data Analytics in Edge-Enabled IoT Systems.. AAAI Spring Symposia, page 305. AAAI Press, (2024)FMLFS: A Federated Multi-Label Feature Selection Based on Information Theory in IoT Environment., and . SMARTCOMP, page 166-173. IEEE, (2024)On the Effectiveness of Standard Centrality Metrics for Interdependent Networks., , , and . ICNC, page 842-846. IEEE, (2019)Smart Edge-Enabled Traffic Light Control: Improving Reward-Communication Trade-offs with Federated Reinforcement Learning., , , and . SMARTCOMP, page 40-47. IEEE, (2022)QoS-Aware Priority-Based Task Offloading for Deep Learning Services at the Edge., , , and . CCNC, page 319-325. IEEE, (2022)Enhancing IoT Security: A Novel Feature Engineering Approach for ML-Based Intrusion Detection Systems., and . CoRR, (2024)Edge Layer Design and Optimization for Smart Grids., , , , and . SmartGridComm, page 1-6. IEEE, (2020)