![](https://img.haomeiwen.com/i14491816/c3be518040061e6f.png)
优化的问题:梯度消失、局部最优
梯度消失、梯度爆炸
![](https://img.haomeiwen.com/i14491816/668b493c7421b6a7.png)
局部最优:
![](https://img.haomeiwen.com/i14491816/974a40cb83ac250c.png)
![](https://img.haomeiwen.com/i14491816/dfb73245f3038d45.png)
![](https://img.haomeiwen.com/i14491816/0835bb2c4b32483c.png)
梯度下降
![](https://img.haomeiwen.com/i14491816/6b2d6815feedea6c.png)
![](https://img.haomeiwen.com/i14491816/f87d468e401a015f.png)
![](https://img.haomeiwen.com/i14491816/5585ecc9914f86a9.png)
梯度下降的优化影响
![](https://img.haomeiwen.com/i14491816/e36415f026a1a8a3.png)
![](https://img.haomeiwen.com/i14491816/627582e6c68ebb0f.png)
![](https://img.haomeiwen.com/i14491816/ecdc3573c525963d.png)
大小选择
![](https://img.haomeiwen.com/i14491816/65c46f965f8f6da5.png)
指数加权平均(梯度下降算法本身的优化)
![](https://img.haomeiwen.com/i14491816/65595b708e335709.png)
![](https://img.haomeiwen.com/i14491816/7d93da7fad34e908.png)
![](https://img.haomeiwen.com/i14491816/adb4d1254da0f81e.png)
![](https://img.haomeiwen.com/i14491816/5ad32e04fd88f3d1.png)
![](https://img.haomeiwen.com/i14491816/6656f07dedc0eb1a.png)
![](https://img.haomeiwen.com/i14491816/181221a0902fd8fd.png)
权重越大,曲线越平滑,权重越小,曲线越曲折
![](https://img.haomeiwen.com/i14491816/89a67a9bacc20e94.png)
动量梯度下降法
![](https://img.haomeiwen.com/i14491816/256e8608f11f33b4.png)
这样的梯度下降有什么变化:
![](https://img.haomeiwen.com/i14491816/24c26d315ef93680.png)
![](https://img.haomeiwen.com/i14491816/0346c652b08c6bef.png)
RMSProp算法
![](https://img.haomeiwen.com/i14491816/03afa46c59fb2da3.png)
![](https://img.haomeiwen.com/i14491816/27671ff5bace527f.png)
Adam算法
![](https://img.haomeiwen.com/i14491816/72bd075a137097e9.png)
![](https://img.haomeiwen.com/i14491816/41121a6ab9e0258f.png)
![](https://img.haomeiwen.com/i14491816/a8e033bbcb51be81.png)
![](https://img.haomeiwen.com/i14491816/a09111234e5d0305.png)
![](https://img.haomeiwen.com/i14491816/aac23b90cd90c889.png)
tensorflow Adam算法API
![](https://img.haomeiwen.com/i14491816/d587b60e1cffe17f.png)
学习率衰减
![](https://img.haomeiwen.com/i14491816/107c6d97e1c9d29d.png)
标准化输入
![](https://img.haomeiwen.com/i14491816/3e2acfcf2fc5ebd8.png)
![](https://img.haomeiwen.com/i14491816/41b7db6acb4827a3.png)
![](https://img.haomeiwen.com/i14491816/63ca90870ce3883e.png)
![](https://img.haomeiwen.com/i14491816/cc5dc566fd5e07ec.png)
![](https://img.haomeiwen.com/i14491816/6a53fcd25c9230f8.png)
代码练习
动量梯度下降
![](https://img.haomeiwen.com/i14491816/588a4ed5f82375a8.png)
公式中的s在代码中定义成了v
![](https://img.haomeiwen.com/i14491816/13306322631b9493.png)
更新Adam算法网络的参数
![](https://img.haomeiwen.com/i14491816/41121a6ab9e0258f.png)
![](https://img.haomeiwen.com/i14491816/e1dbe6bf9b0b93bc.png)
![](https://img.haomeiwen.com/i14491816/faa636a11ae824a0.png)
![](https://img.haomeiwen.com/i14491816/99085946e6a19b36.png)
![](https://img.haomeiwen.com/i14491816/072dc13f73c6db8c.png)
优化的问题:梯度消失、局部最优
局部最优:
梯度下降
大小选择
权重越大,曲线越平滑,权重越小,曲线越曲折
这样的梯度下降有什么变化:
公式中的s在代码中定义成了v
本文标题:梯度下降算法改进
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