SpaFL: Communication-Efficient Federated Learning with Sparse Models and Low Computational Overhead
–Neural Information Processing Systems
The large communication and computation overhead of federated learning (FL) is one of the main challenges facing its practical deployment over resource-constrained clients and systems.
Neural Information Processing Systems
Oct-10-2025, 11:21:31 GMT
- Country:
- North America > United States
- Virginia (0.04)
- Asia > China
- Tianjin Province > Tianjin (0.04)
- Ningxia Hui Autonomous Region > Yinchuan (0.04)
- North America > United States
- Genre:
- Research Report > Experimental Study (0.93)
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- Information Technology > Security & Privacy (0.46)
- Technology: