Deep Learning Networks: Advantages of ReLU over Sigmoid Function
Sigmoid: tend to vanish gradient (cause there is a mechanism to reduce the gradient as "a" increases, where "a" is the input of a sigmoid function. When "a" grows to infinite large, S′(a) S(a)(1 S(a)) 1 (1 1) 0.
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