【Deep Learning】笔记：Understanding the difficulty of training deep feedforward neural networks
这几天读了这篇论文，在这里将大致内容写在这里。 Abstract 介绍这篇论文的主要内容就是尝试更好的理解为什么使用“标准随机初始化”来计算使用标准梯度下降的网络效果通常来讲都不是很好。 首先研究了不同的非线性激活函数的影响，发现 sigmoid 函数它的均值会导致在隐层中很容易到达函数的饱和区域，因此sigmoid 激活函数在随机初始化的深度网络中并不合适。但同时惊喜的发现，处于饱和的神经元能够
相关文章
- 1. Xavier——Understanding the difficulty of training deep feedforward neural networks
- 2. 论文解析-《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. [论文笔记] [2010] Understanding the Difficulty of Training Deep Feedforward Neural Networks
- 5. 神经网络不同激活函数比较--读《Understanding the difficulty of training deep feedforward neural networks》
- 6. Exploring the teaching of deep learning in neural networks
- 7. Neural Networks and Deep Learning 学习笔记（一）
- 8. Neural Networks and Deep Learning
- 9. On the difficulty of training Recurrent Neural Networks
- 10. 理解训练深层前馈神经网络的难度（Undetanding the difficulty of training deep feedforward neural networks ）...
- 更多相关文章...
- • XSLT
- • ASP.NET Razor - 标记 - ASP.NET 教程
- • Tomcat学习笔记（史上最全tomcat学习笔记）
- • Java Agent入门实战（三）-JVM Attach原理与使用
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Xavier——Understanding the difficulty of training deep feedforward neural networks
- 2. 论文解析-《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. [论文笔记] [2010] Understanding the Difficulty of Training Deep Feedforward Neural Networks
- 5. 神经网络不同激活函数比较--读《Understanding the difficulty of training deep feedforward neural networks》
- 6. Exploring the teaching of deep learning in neural networks
- 7. Neural Networks and Deep Learning 学习笔记（一）
- 8. Neural Networks and Deep Learning
- 9. On the difficulty of training Recurrent Neural Networks
- 10. 理解训练深层前馈神经网络的难度（Undetanding the difficulty of training deep feedforward neural networks ）...