Data-oriented optimized nonuniform quantization for CR-enhanced communication efficiency in federated learning
Abstract This paper proposes a novel communication-efficient framework based on nonuniform-quantized federated learning (Non-QuanFL) for federated learning (FL), which leverages optimized nonuniform quantization to reduce the communication overhead while preserving model accuracy. In this framework,...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-06-01
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| Series: | EURASIP Journal on Wireless Communications and Networking |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13638-025-02471-y |
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