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Hiding in the Crowd: Federated Data Augmentation for On-Device Learning.

, , , , , and . IEEE Intell. Syst., 36 (5): 80-87 (2021)

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LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning., , , , , , and . WWW, page 3347-3357. ACM, (2022)Federated Knowledge Distillation., , , , and . CoRR, (2020)Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup., , , , , and . CoRR, (2020)Mix2SFL: Two-Way Mixup for Scalable, Accurate, and Communication-Efficient Split Federated Learning., , , , , , and . IEEE Trans. Big Data, 10 (3): 238-248 (June 2024)Distilling On-Device Intelligence at the Network Edge., , , , , , , , and . CoRR, (2019)Multi-hop Federated Private Data Augmentation with Sample Compression., , , , , and . CoRR, (2019)Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data., , , , , and . CoRR, (2018)SplitAMC: Split Learning for Robust Automatic Modulation Classification., , and . VTC2023-Spring, page 1-6. IEEE, (2023)Hiding in the Crowd: Federated Data Augmentation for On-Device Learning., , , , , and . IEEE Intell. Syst., 36 (5): 80-87 (2021)Poster: Location-based Directional CSMA/CA for Millimeter Wave V2V Communications., , and . VNC, page 1-2. IEEE, (2018)