Federated Learning with Non-IID Data 論文筆記
Federated Learning with Non-IID Data 論文筆記 原文翻譯參考：https://blog.csdn.net/GJ_007/article/details/104632718算法 論文經過實驗驗證了，在non-IID數據中，使用FedAvg算法訓練的模型會使準確率下降。.net 從圖中能夠看出在non-IID使用FedAvg算法訓練的模型準確率有了明顯的降低，可是對
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相關文章
- 1. Federated Learning with Non-IID Data 論文筆記
- 2. Secure Federated Transfer Learning（論文筆記）
- 3. Federated Learning with Non-IID Data
- 4. SecureBoost: A Lossless Federated Learning Framework論文筆記
- 5. 論文筆記Client-Edge-Cloud Hierarchical Federated Learning
- 6. 論文筆記——Fair Resource Allocation in Federated Learning
- 7. Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data 論文閱讀筆記
- 8. 論文筆記——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 9. Federated Machine Learning:Concept and Applications(論文筆記)
- 10. 【論文筆記】《FLchain: Federated Learning via MEC-enabled Blockchain Network》精讀筆記