Communication-Efficient Learning of Deep Networks from Decentralized Data
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 Abstractgit 現代移動設備能夠訪問大量適合模型學習的數據，從而大大改善設備上的用戶體驗。例如，語言模型能夠改善語音識別和文本輸入，圖像模型能夠自動選擇好的照片。然而，這些豐富的數據每每對隱私敏感，數量龐大，或者二者兼而有之，這可能會妨礙登陸到數據中心並使用傳統方法進行訓練。咱們提倡一種替代方法，將訓練數據分佈在
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相關文章
- 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
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- 10. An Overview of Multi-Task Learning in Deep Neural Networks