摘要: Modern mobile devices have access to a wealth of data suitable for learning models, which in turn can greatly improve the user experience on the device. For example, language models can improve speech recognition and text entry, and image …
威胁模型:
方案应满足的安全需求: 设计目标: 动态累加器:
具体方案:
A. Initialization B. Pseudonym Generation C. Genesis Block Generation
D. Registration
E. Local Model Signature GenerationF . Local Model V erif…
Balancing Computation Speed and Quality: A Decentralized Motion Planning Method for Cooperative Lane Changes of Connected and Automated Vehicles
参考资料来源:《Balancing Computation Speed and Quality: A Decentralized Motion Planning Method for …
Communication-Efficient Learning of Deep Networks from Decentralized Data 这篇文章算是联邦学习的开山之作吧,提出了FedAvg的算法,文中对比了不同客户端本地训练次数,客户端训练数据集划分的影响。 0. Abstract
现代移动设备可以获取大…
GDSRec:Graph-Based Decentralized Collaborative Filtering for Social Recommendation
摘要——基于 user-item interactions和user-user social relations生成推荐是基于 web 的系统中的常见用例。这些联系可以自然地表示为图结构数据,因此利用图神经…
Communication-Efficient Learning of Deep Networks from Decentralized Data
论文地址:https://arxiv.org/abs/1602.05629
Abstract
现代移动设备能访问到的大量数据都十分适合于学习模型,并且基于此页可以反过来改善用户在该设备上的体验。例如&am…
原文链接:Communication-Efficient Learning of Deep Networks from Decentralized Data (mlr.press)
该论文是最早提出联邦学习的论文,作者结合背景提出了联邦平均的算法,并作了相应验证实验。
ABS
随着移动设备的用户增加,产…