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FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients., , , , , , , , and . CoRR, (2024)Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates., , , and . CoRR, (2023)ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity., , , , , and . CoRR, (2022)FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition., , and . INTERSPEECH, page 1678-1682. ISCA, (2020)vFedSec: Efficient Secure Aggregation for Vertical Federated Learning via Secure Layer., , , , , and . CoRR, (2023)High-throughput Simulation of Federated Learning via Resource-Aware Client Placement., , , , , , , and . CoRR, (2023)A first look into the carbon footprint of federated learning., , , , , and . CoRR, (2020)A First Look into the Carbon Footprint of Federated Learning., , , , , , , , and . J. Mach. Learn. Res., (2023)A first look into the carbon footprint of federated learning., , , , , , , and . CoRR, (2021)FedVal: Different good or different bad in federated learning., , , , and . USENIX Security Symposium, page 6365-6380. USENIX Association, (2023)