但它们仍然可以加入同一个FL system。比如可以运用multi-task learning的思想来解决这类问题。
联邦学习(Federated Learning, FL)作为一种新兴技术,可以在保持数据去中心化的同时协同训练共享模型,是数据孤岛的合理解决方案。而将联邦学习应用到 GNN 的训练上,则称为 图联邦学习(Federated Graph Learning,FGL)。本篇论文按照图数据在客户端之间的分布方式,将 FGL 划分如下: 图间联邦(inter-graph FL) 图内联邦...
First, based on the ability of the GCN to process non-Euclidean spatial data, this paper proposes a GCN to build local models for federated learning clients. The difference between the GCN proposed in this paper and the classical GCN is the fact that TopK graph pooling layers and full ...
文章提出了FedAc算法 - FedAc is the first provable acceleration of FedAvg that improves convergence speed and communication efficiency on various types of convex functions. Inverting Gradients - How easy is it to break privacy in federated learning? Jonas Geiping (University of Siegen) · Hartmut Bau...
26 FedCVD: The First Real-World Federated Learning Benchmark on Cardiovascular Disease Data Yukun Zhang, Guanzhong Chen, Zenglin Xu, Jianyong Wang, Dun Zeng, Junfan Li, Jinghua Wang, Yuan Qi, Irwin King 2024-10-28 arXiv https://github.com/SMILELab-FL/FedCVD http://arxiv.org/abs/2411.07...
Data PoisoningFederated Learning Datasets Add Datasetsintroduced or used in this paper Results from the Paper Edit AddRemove Submitresults from this paperto get state-of-the-art GitHub badges and help the community compare results to other papers. ...
it is essential to establish a mechanism for verifying the ownership of the model and as well tracing its origin to the leaker among the FL participants. In this paper, we present FedTracker, the first FL model protection framework that provides both ownership verification and traceability. FedTr...
The artificial intelligence revolution has been spurred forward by the availability of large-scale datasets. In contrast, the paucity of large-scale medical datasets hinders the application of machine learning in healthcare. The lack of publicly availabl
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi...
Robust and Privacy-Preserving Decentralizd Deep Federated Learning Training Focusing on Digital Healthcare Applications 本文提出FedAVG的分布式训练替代品,将多卡训练的Ring-Allreduce引入联邦学习中,并且用CRT阈值密钥分享解决掉线和隐私泄露问题。但性能上RPDFL与FedAVG持平,并没有展现出特别优势。优势大概是减少了服务...