图解maxout-带参数的激活函数

Maxout 单元是一个激活函数，它本身是由我们的模型训练的。单个 Maxout 单元可以解释为对任意凸函数进行（分段）线性逼近。

Learnable activation function [ lan J. Goodfellow, ICML'13]
Activation function in maxout network can be any piecewise linear convex function How many pieces depending on how many elements in a group.

Maxout 单元取“ n 个线性函数”的值中的最大值。线性函数（件）的数量是预先确定的。

 参考链接：

https://www.youtube.com/watch?v=xki61j7z-30&list=PLJV_el3uVTsPy9oCRY30oBPNLCo89yu49&index=17&t=1581s&ab_channel=Hung-yiLeehttps://www.youtube.com/watch?v=xki61j7z-30&list=PLJV_el3uVTsPy9oCRY30oBPNLCo89yu49&index=17&t=1581s&ab_channel=Hung-yiLee

https://medium.com/@rahuljain13101999/maxout-learning-activation-function-279e274bbf8ehttps://medium.com/@rahuljain13101999/maxout-learning-activation-function-279e274bbf8e