In particular, this game-changing collaborative framework offers knowledge sharing from diverse data with a privacy-preserving. This chapter will discuss how federated learning can enable the development of an open health ecosystem with the support of AI. Existing challenges and solutions for federated ...
Training supervised machine learning models like deep learning requires high-quality labelled datasets that contain enough samples from various categories
OpenFL is designed to be compatible with any ML or deep learning (DL) framework, and has tutorials and multiple examples using TensorFlow, PyTorch and MXNet. OpenFL combines hardware and software to enable privacy-preserving AI using Intel SGX and Gramine (more on Gramine in the next section)...
(引用格式:Zheng H, Hu H, Han Z. Preserving User Privacy for Machine Learning: Local Differential Privacy or Federated Machine Learning?[J]. IEEE Intelligent Systems, 2020, 35(4): 5-14.) (思考:这篇论文立意比较吸引人,讨论的东西也比较有意思,推荐了解一下,比较适合写在论文引言里面讨论,实验做...
Machine LearningData TechnologyInsurTechRegTechAIMLFederated learning is a pioneering privacy-preserving data technology and also a new machine learning model trained on distributed data sets.Companies cdoi:10.2139/ssrn.3696609mietanka, MagorzataPithadia, Hirsh...
Invited Talk:Yang Liu."Federated Machine Learning: concept and applications". / The First SCRIPTS Workshop on Privacy Preserving Technologies and their Applications 标准 IEEE P3652.1 Guide for Architectural Framework and Application of Federated Machine Learning (联邦学习的框架及应用) . 白皮书及其他 ...
Tackling Data Heterogeneity in Federated Learning with Class Prototypes Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation 联邦学习在 AAAI 2023 会议中的...
In this paper, we propose a privacy-preserving federated learning framework to enhance the privacy of IoHT data. Our approach integrates federated learning with -differential privacy to design an effective and secure intrusion detection system (IDS) for identifying cyberattacks on the network traffic ...
Phan N, Wu X, Hu H, Dou D (2017) Adaptive laplace mechanism: differential privacy preservation in deep learning. In: Proceedings of IEEE ICDM, pp 385–394 Ren H, Li H, Dai Y, Yang K, Lin X (2018) Querying in internet of things with privacy preserving: challenges, solutions and oppo...
本文的方法大体是与图联邦 隐私+推荐:FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation一文一致的,作图上进行了些许优化,具体方法的区别主要体现在以下: 3.1 Problem Formulation 删去了对”模型目标是通过\mathcal{G}_i中的交互数据预测未被观察到的评分矩阵部分(y \in \mathbf{Y\setmi...