Communication-Efficient Learning of Deep Networks from Decentralized Data
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 Abstractgit 现代移动设备能够访问大量适合模型学习的数据，从而大大改善设备上的用户体验。例如，语言模型能够改善语音识别和文本输入，图像模型能够自动选择好的照片。然而，这些丰富的数据每每对隐私敏感，数量庞大，或者二者兼而有之，这可能会妨碍登陆到数据中心并使用传统方法进行训练。咱们提倡一种替代方法，将训练数据分布在
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相关文章
- 1. Communication-Efficient Learning of Deep Networks from Decentralized Data
- 2. LEARNING NOTES FROM DEEP LEARNING
- 3. Fundamentals of Deep Learning – Introduction to Recurrent Neural Networks
- 4. Inspirational Applications of Deep Learning
- 5. Exploring the teaching of deep learning in neural networks
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- 7. Deep Learning 1: Foundations of Convolutional Neural Networks
- 8. Neural Networks and Deep Learning
- 9. Evaluation of Deep Learning Toolkits
- 10. An Overview of Multi-Task Learning in Deep Neural Networks