Paper之DL之BP：《Understanding the difficulty of training deep feedforward neural networks》
Understanding the difficulty of training deep feedforward neural networks Sigmoid的四層侷限 sigmoid函數的test loss和training loss要經過很多輪數一直爲0.5，後再有到0.1的差強人意的變化。 We hypothesize that this behavior is due t
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相關文章
- 1. Xavier——Understanding the difficulty of training deep feedforward neural networks
- 2. 【Deep Learning】筆記：Understanding the difficulty of training deep feedforward neural networks
- 3. 論文解析-《Understanding the difficulty of training deep feedforward neural networks》
- 4. [論文筆記] [2010] Understanding the Difficulty of Training Deep Feedforward Neural Networks
- 5. On the difficulty of training Recurrent Neural Networks
- 6. 神經網絡不同激活函數比較--讀《Understanding the difficulty of training deep feedforward neural networks》
- 7. 神經網絡剖析激活函數優缺點（Undetanding the difficulty of training deep feedforward neural networks）
- 8. 理解訓練深層前饋神經網絡的難度（Undetanding the difficulty of training deep feedforward neural networks ）...
- 9. Exploring the teaching of deep learning in neural networks
- 10. Understanding Neural Networks Through Deep Visualization