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SEM: A Simple Yet Efficient Model-agnostic Local Training Mechanism to Tackle Data Sparsity and Scarcity in Federated Learning., , , , , and . candar, page 120-126. IEEE, (2023)Spatial-temporal Coverage Maximization in Vehicle-based Mobile Crowdsensing for Air Quality Monitoring., , , , and . WCNC, page 1449-1454. IEEE, (2022)Topology-aware Sparse Allreduce for Large-scale Deep Learning., , and . IPCCC, page 1-8. IEEE, (2019)FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection., , , , , , and . IJCNN, page 1-10. IEEE, (2023)Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning., , , , , , , and . IPDPS, page 1085-1096. IEEE, (2022)Enhancing the Generalization of Personalized Federated Learning with Multi-head Model and Ensemble Voting., , , , , , and . IPDPS, page 205-216. IEEE, (2024)Scalable Low-Latency Inter-FPGA Networks., , , , and . IPDPS, page 234-245. IEEE, (2022)An Allreduce Algorithm and Network Co-design for Large-Scale Training of Distributed Deep Learning., and . CCGRID, page 396-405. IEEE, (2021)High Accurate and Explainable Multi-Pill Detection Framework with Graph Neural Network-Assisted Multimodal Data Fusion., , , , , and . CoRR, (2023)A data-driven approach for high accurate spatiotemporal precipitation estimation., , , , , and . Neural Comput. Appl., 36 (11): 6099-6118 (April 2024)