論文解析-《Understanding the difficulty of training deep feedforward neural networks》
這篇論文詳細解析了深度網絡中參數xavier初始化方法，這裏做一下讀書筆記，同時記錄一下自己的理解。 1 引言 經典前饋神經網絡其實很早就有了（Remelhart et al.,1986），近年來對深度監督神經網絡的一些成果只不過在初始化和訓練方法跟以前有點區別，可是爲什麼能夠取得這麼好的結果？部分原因可能是使用非監督訓練方法來初始化網絡，使得網絡整體處於一個比較好的優化狀態。但是更早的一些研究(
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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. Paper之DL之BP：《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. Understanding Neural Networks Through Deep Visualization 論文筆記
- 10. Understanding Neural Networks Through Deep Visualization