Federated Learning with Non-IID Data 论文笔记
Federated Learning with Non-IID Data 论文笔记 原文翻译参考：https://blog.csdn.net/GJ_007/article/details/104632718 论文通过实验验证了，在non-IID数据中，使用FedAvg算法训练的模型会使准确率降低。 从图中可以看出在non-IID使用FedAvg算法训练的模型准确率有了明显的下降，但是对于IID数据
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相关文章
- 1. Federated Learning with Non-IID Data 论文笔记
- 2. Secure Federated Transfer Learning（论文笔记）
- 3. Federated Learning with Non-IID Data
- 4. SecureBoost: A Lossless Federated Learning Framework论文笔记
- 5. 论文笔记Client-Edge-Cloud Hierarchical Federated Learning
- 6. 论文笔记——Fair Resource Allocation in Federated Learning
- 7. Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data 论文阅读笔记
- 8. 论文笔记——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 9. Federated Machine Learning:Concept and Applications(论文笔记)
- 10. 【论文笔记】《FLchain: Federated Learning via MEC-enabled Blockchain Network》精读笔记