2.3.3 FederatedTransfer Learning (FTL) 2.4 Architecture for a federated learning system 2.4.1 Horizontal Federated Learning 2.4.2 Vertical Federated Learning 2.4.3 FederatedTransfer Learning 2.4.4 Incentives Mechanism 3 RELATEDWORKS 3.1 Privacy-preserving machine learning 3.2 Federated Learning vs Distribut...
Definition of Federated Learning Privacy of Federated Learning A Categorization of Federated Learning Architecture for a federated learning system RELATED WORKS Privacy-preserving machine learning Federated Learning vs Distributed Machine Learning Federated Learning vs Edge Computing Federated Learning vs Federated...
An overview of federated learning difinition of federated learning privacy of federated learning a categorization of federated learning architecture for a federated learning system Related works privacy-preserving machine learning federated learning vs. distributed machine learning federated learning vs. edge co...
[1] Martin Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang. 2016. Deep Learning with Differential Privacy. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS ’16). ACM, New York, NY, USA, 308–318...
微众银行 (WebBank) 进一步提出了联邦迁移学习(Federated Transfer Learning,FTL)[1,6]。FTL 通过应用同态加密(Homomorphic Encryption)和多项式近似代替差分隐私(Polynomial Approximation instead of Differential Privacy)的方法,为特定行业提供了一种更安全、更可靠的方法。与此同时,基于迁移学习的的特性,FTL 的参与方可...
Federated Machine Learning: Concept and Applications Authors QIANG YANG,YANG LIU,TIANJIAN CHEN,YONGXIN TONG Keywords Federated learning,GDPR,transfer
联邦机器学习(Federated machine learning/Federated Learning),又名联邦学习,联合学习,联盟学习。联邦机器学习是一个机器学习框架,能有效帮助多个机构在满足用户隐私保护、数据安全和政府法规的要求下,进行数据使用和机器学习建模。 举例来说,假设有两个不同的企业A 和 B,它们拥有不同数据。比如,企业 A 有用户特征数据...
(DMO).Furthermore,we propose a novel framework called federated mutual learning(FML),which enables each client to train a personalized model that accounts for the data heterogeneity(DH).A"meme model"serves as an intermediary between the personalized and global models to address model heterogeneity(...
联邦学习——论文研究(FedML: A Research Library and Benchmark for Federated Machine Learning),主要内容:该篇论文提出了一个联邦学习框架——FedML,该框架支持三种计算范式:on-devicetrainingforedgedevicesdistributedcomputingsingle-machinesimulation强调联邦
Awesome Federated Machine Learning Federated Learning (FL) is a new machine learning framework, which enables multiple devices collaboratively to train a shared model without compromising data privacy and security. This repository aims to keep tracking the latest research advancements of federated learning...