Federated Machine Learning: Concept and Applications
郑重声明：原文参见标题，若有侵权，请联系做者，将会撤销发布！html 今天的人工智能仍然面临两大挑战。一种是，在大多数行业中，数据以孤岛的形式存在。二是增强数据隐私和安全。咱们提出了一个解决这些挑战的可能方案：安全联邦学习。除了谷歌在2016年首次提出的联邦学习框架外，咱们还引入了一个全面的安全联邦学习框架，其中包括横向联邦学习、纵向联邦学习和联邦迁移学习。咱们为联邦学习框架提供定义、架构
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相关文章
- 1. Federated Machine Learning:Concept and Applications
- 2. Federated Machine Learning:Concept and Applications(论文笔记)
- 3. Kernel Functions for Machine Learning Applications
- 4. 【译】Federated Learning: Bringing Machine Learning to the edge with Kotlin and Android
- 5. Reinforcement Learning Note: Concept and MDP
- 6. Learning Machine Learning, Part 2: Algorithms and Techniques
- 7. Machine and Deep Learning with Python
- 8. Best Machine Learning Applications: Ideas for Mobile Apps
- 9. Federated Learning: 相关
- 10. On the use of machine learning to predict the time and resources consumed by applications