Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatic
Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatics阅读笔记 文献背景及解决问题 车联网中的联邦学习 具体方案 总结与思考 文献背景及解决问题 由于无线网络带宽和计算资源的限制，车辆很难使用大量数据来进行提高服务质量的机器学习，比如自动驾驶和交通预测
相关文章
- 1. Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatic
- 2. 论文笔记——Federated learning framework for mobile edge computing networks
- 3. Federated Learning in Mobile Edge Networks: AComprehensive Survey(翻译)
- 4. Differentially Private Federated Learning: A Client Level Perspective
- 5. 论文笔记——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 6. Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 7. Deployment Characteristics of "The Edge" in Mobile Edge Computing
- 8. 【论文阅读】Edge Computing Architecture for Mobile Crowdsensing
- 9. Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach
- 10. Edge Computing
- 更多相关文章...
- • Swift for-in 循环 - Swift 教程
- • Lua for 循环 - Lua 教程
- • Java Agent入门实战（三）-JVM Attach原理与使用
- • Java Agent入门实战（一）-Instrumentation介绍与使用
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatic
- 2. 论文笔记——Federated learning framework for mobile edge computing networks
- 3. Federated Learning in Mobile Edge Networks: AComprehensive Survey(翻译)
- 4. Differentially Private Federated Learning: A Client Level Perspective
- 5. 论文笔记——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 6. Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 7. Deployment Characteristics of "The Edge" in Mobile Edge Computing
- 8. 【论文阅读】Edge Computing Architecture for Mobile Crowdsensing
- 9. Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach
- 10. Edge Computing