Paper之DL之BP：《Understanding the difficulty of training deep feedforward neural networks》
Understanding the difficulty of training deep feedforward neural networks Sigmoid的四层局限 sigmoid函数的test loss和training loss要经过很多轮数一直为0.5，后再有到0.1的差强人意的变化。 We hypothesize that this behavior is due t
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相关文章
- 1. Xavier——Understanding the difficulty of training deep feedforward neural networks
- 2. 【Deep Learning】笔记：Understanding the difficulty of training deep feedforward neural networks
- 3. 论文解析-《Understanding the difficulty of training deep feedforward neural networks》
- 4. [论文笔记] [2010] Understanding the Difficulty of Training Deep Feedforward Neural Networks
- 5. On the difficulty of training Recurrent Neural Networks
- 6. 神经网络不同激活函数比较--读《Understanding the difficulty of training deep feedforward neural networks》
- 7. 神经网络剖析激活函数优缺点（Undetanding the difficulty of training deep feedforward neural networks）
- 8. 理解训练深层前馈神经网络的难度（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