PELU

2000년 도입 · 논문 2편에서 사용

Parameterized Exponential Linear Units, or PELU, is an activation function for neural networks. It involves learning a parameterization of ELU in order to learn the proper activation shape at each layer in a CNN. The PELU has two additional parameters over the ELU: $$ f\left(x\right) = cx \text{ if } x > 0 $$ $$ f\left(x\right) = \alpha\exp^{\frac{x}{b}} - 1 \text{ if } x \leq 0 $$ Where $a$, $b$, and $c > 0$. Here $c$ causes a change in the slope in the positive quadrant, $b$ controls the scale of the exponential decay, and $\alpha$ controls the saturation in the negative quadrant. Source: Activation Functions

출처: Parametric Exponential Linear Unit for Deep Convolutional Neural Networks

소개 논문: Parametric Exponential Linear Unit for Deep Convolutional Neural Networks