Adaptive Sparsification and Quantization for Enhanced Energy Efficiency in Federated Learning
Federated learning is a distributed learning framework that operates effectively over wireless networks. It enables devices to collaboratively train a model over wireless links by sharing model parameters rather than personal data. However, a key challenge in federated learning arises from the limit...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
IEEE
2024-01-01
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| シリーズ: | IEEE Open Journal of the Communications Society |
| 主題: | |
| オンライン･アクセス: | https://ieeexplore.ieee.org/document/10589557/ |
| タグ: |
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