Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach
论文解读：html 背景 开销和隐私两大problems 移动网络在计算和通讯两方面有极大的开销，若是没有激励机制，那么感兴趣的移动设备就不肯意加入联邦学习任务web 以往的假设是认为全部的移动设备都会在被邀请时无条件的参与联邦学习，可是没有精心设计的补偿，自私自利的移动设备将不肯意参与网络 两个信息不对成 1.任务发布者不知道用于模型训练的资源量和数据大小 2.不知道移动设备的数据质量 致使：
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相关文章
- 1. Federated Learning in Mobile Edge Networks: AComprehensive Survey(翻译)
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- 6. Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
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- 10. 论文泛读 A Novel Ensemble Learning-based Approach for Click Fraud Detection in Mobile Advertising [1/10]