3.1 Privacy-preserving machine learning 3.2 Federated Learning vs Distributed Machine Learning 3.3 Federated Learning vs Edge Computing 3.4 Federated Learning vs Federated Database Systems 4 APPLICATIONS 5 FEDERATED LEARNING AND DATA ALLIANCE OF ENTERPRISES 6 CONCLUSIONS AND PROSPECTS 写在后面 写在前面 大家...
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...
2017年4月6日,谷歌科学家Brendan McMahan和Daniel Ramage在GoogleAI上发布名为《 Federated Learning: Collaborative Machine Learning without Centralized Training Data》的博文,介绍了Federated Learning也是一种机器学习,能够让用户通过移动设备交互来训练模型。 Google近期还特别推出中文漫画对于Federated Learning进行介绍,...
Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth. 2017. Practical Secure Aggregation for Privacy-Preserving Machine Learning. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security (CCS ’17). ACM, New York, NY, USA, 1175–1191. https://doi.org...
联邦机器学习可以看作是保护隐私的分散协作机器学习(privacy-preserving decentralized collaborative machine learning),与多方保密的机器学习(multi-party privacy mechine learning)密切相关。Federated Learning vs Distributed Machine Learning第一眼看上去,水平联邦学习很像分布式机器学习(distributed machine learning)。分布式...
federated learning vs. distributed machine learning federated learning vs. edge computing federated learning vs. federated database systems Applications Federated learning and data alliance of enterprises Conclusions and prospects Introduction 当今的AI仍然面临两个主要挑战。 一是在大多数行业中,数据以孤立的孤岛...
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...
Centralized vs decentralized vs federated machine learning Federated learning frameworks Federated learning applications Key federated learning limitations and things to consider 1Comment Share Stay tuned to the latest industry updates. By clicking subscribe you confirm, that you understand and agree to the...
Decentralized vs. Federated Machine Learning To understand federated machine learning better, we need to understand how a centralized, decentralized approach works to perform ML. Centralized Machine Learning In the traditional machine learning approach, data for machine learning models were initially ...
It is also very useful for organizations looking to conduct machine learning in heavily-regulated sectors, such as the finance or healthcare sectors, which need to be extremely cautious about processingpersonally identifiable information(PII), patient health information, payment details, or other regulat...