Federated Machine Learning: Concept and Applications
鄭重聲明：原文參見標題，若有侵權，請聯繫做者，將會撤銷發佈！html 今天的人工智能仍然面臨兩大挑戰。一種是，在大多數行業中，數據以孤島的形式存在。二是增強數據隱私和安全。咱們提出了一個解決這些挑戰的可能方案：安全聯邦學習。除了谷歌在2016年首次提出的聯邦學習框架外，咱們還引入了一個全面的安全聯邦學習框架，其中包括橫向聯邦學習、縱向聯邦學習和聯邦遷移學習。咱們爲聯邦學習框架提供定義、架構
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相關文章
- 1. Federated Machine Learning:Concept and Applications
- 2. Federated Machine Learning:Concept and Applications(論文筆記)
- 3. Kernel Functions for Machine Learning Applications
- 4. 【譯】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: 相關
- 10. On the use of machine learning to predict the time and resources consumed by applications