联邦学习---学习笔记（一）

联邦学习

主要内容
1、研究背景
2、定义及模型
3、存在的问题
4、模型的优化

为了进一步的理解模型机制，下面介绍了一个简单的神经网络模型–多层感知器

参考文献及参考链接
[1] https://zhuanlan.zhihu.com/p/532555889.
[2] Zhu H, Jin Y. Multi-objective evolutionary federated learning[J]. IEEE transactions on neural networks and learning systems, 2019, 31(4): 1310-1322. (IF= 14.255 Q1).
[3] Pham D T. Neural networks in engineering[J]. WIT Transactions on Information and Communication Technologies, 1970, 6.
[4] https://zhuanlan.zhihu.com/p/63184325.
[5] https://blog.csdn.net/weixin_40857506/article/details/121009503.
[6] McMahan B, Moore E, Ramage D, et al. Communication-efficient learning of deep networks from decentralized data[C]//Artificial intelligence and statistics. PMLR, 2017: 1273-1282.
[7] Li L, Fan Y, Tse M, et al. A review of applications in federated learning[J]. Computers & Industrial Engineering, 2020, 149: 106854.