大家好,今天说的这篇论文是2020年FL-IJCAI'20 workshop的《Collaborative Fairness in Federated Learning》,一篇很简短易懂的论文 一句话总结:这篇论文提出CFFL框架,根据参与者的声誉收敛到不同模型,实现联邦学习公平协作 论文地址在这:arxiv.org/abs/2008.1216 其他联邦学习公平性论文: 反向人:联邦学习激励机制综述...
这篇论文提出CFFL框架,根据参与者的声誉收敛到不同模型,实现联邦学习公平协作 参考笔记:https://zhuanlan.zhihu.com/p/600343559 方法:衡量声誉标准:参与方上传的梯度质量
This problem can be addressed by Distributed or Federated Learning (FL) that leverages a parameter server to aggregate model updates from individual participants. However, most existing Distributed or FL frameworks have overlooked an important aspect of participation: collaborative fairness. In particular,...
This problem can be addressed by Distributed or Federated Learning (FL) that leverages a parameter server to aggregate model updates from individual participants. However, most existing Distributed or FL frameworks have overlooked an important aspect of participation: collaborative fairness. In particular,...
Despite its potential, it presents several drawbacks such as heterogeneity of data distributions across nodes, ensuring model fairness, and addressing privacy concerns in highly regulated industries like finance and healthcare. The massive volumes of data involved and the requirement for a real-time res...
This equation indicates that our objective is to find P local models which achieve both their own global minima and fairness simultaneously. Since we tested the local models on the shared test data, each participant’s global minima and fairness were compatible. In addition, we defined the ...
Even though more in-depth investigations on the accuracy-privacy-cost balance should be conducted, we emphasize that the proposed federated machine learning framework tackles the common concerns in collaborative learning, including privacy, efficiency, and fairness, which can be addressed consistently and...
In this section, we have developed a reputation scheme considering possible contributing factors in a worker’s competency and performance to maintain maximum fairness in worker selection. We have also developed a meta-heuristic Particle Swarm Optimization (PSO) based team formation mechanism. And final...
fairness and optimal stochastic control for heterogeneous networks. ieee/acm trans netw 16(2):396–409 article google scholar download references acknowledgements the authors would like to thank the anonymous reviewers for their insightful comments and suggestions on improving this paper. ...
His research interests include deep learning, UAV cluster intelligence and UAV collaborative inference. Qi-Hui Wureceived the B. Sc. degree in communications engineering, and the M. Sc. and Ph. D. degrees in communications and information systems from Institute of Communications Engineering, China ...