[ICLR2022] Efficient Split-Mix federated learning for in-situ model customization during both training and testing time
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Updated
Apr 12, 2023 - Python
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heterofl
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HeteroFL with transfer learning. Clients of differing capacity train slices of one global model at different widths, so weak devices are not excluded.
deep-learning transfer-learning distributed-machine-learning federated-learning heterogeneous-computing privacy-preserving-machine-learning heterofl model-heterogeneity
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Updated
Nov 14, 2024 - Jupyter Notebook
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