without violating privacy laws, we introduce Swarm Learning鈥攁 decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. ...
In the past 2 years, this limitation of FL has been addressed by a new group of decentralized learning technologies, including blockchain FL25and SL26. In SL, AI models are trained locally, and models are combined centrally without requiring central coordination. By using blockchain-based coo...
1.Warnat-Herresthal, Stefanie et al. “SwarmLearning for decentralized and confidential clinical machine learning.” Nature,10.1038/s41586-021-03583-3. 26 May. 2021 2.https://www.sciencedaily.com/releases/2021/05/21052613212...
Swarm Learning for decentralized and confidential clinical machine learning 群体学习:用于去中心化和隐私加密的临床机器学习 基本信息 期刊 / 会议:Nature 作者:Stefanie Warnat-Herresthal,
1.Warnat-Herresthal, Stefanie et al. “SwarmLearning for decentralized and confidential clinical machine learning.” Nature,10.1038/s41586-021-03583-3. 26 May. 2021 2.https://www.sciencedaily.com/releases/2021/05/210526132126.htm --- End ---...
“Demystifying Swarm Learning: A New Paradigm of Blockchain-based Decentralized Federated Learning” (2023). [2]Stefanie Warnat-Herresthal et al. “Swarm Learning for decentralized and confidential clinical machine learning..” (2021). [3]登上Nature封面的群体学习,无需中央协调员,比联邦学习更优秀...
视频中提到的论文名称:Swarm Learning for decentralized and confidential clinical machine learning,2021年5月26日发表在Nature上。论文地址:nature.com/articles/s41。 2021-11-07 回复喜欢 帕帕科技喵 作者 2021-11-08 回复喜欢 登录知乎,您可以享受以下权益: ...
[1] Swarm Learning for decentralized and confidential clinical machine learning [2]https://github.com/HewlettPackard/swarm-learning [3] What is swarm learning? AI, Blockchain and IoT working together to uncover real-time intelligence 原文作者:Vinicius Monteiro ...
SWARM LEARNING Product version: 2.2.0 Swarm Learning is a decentralized, privacy-preserving Machine Learning framework. This framework utilizes the computing power at, or near, the distributed data sources to run the Machine Learning algorithms that train the models. It uses the security of a block...
Machine learning models offer the capability to forecast future energy production or consumption and infer essential unknown variables from existing data. However, legal and policy constraints within specific energy sectors render the data sensitive, presenting technical hurdles in utilizing data from ...