Hard Sigmoid
Hard Sigmoid
The **Hard Sigmoid** is an activation function used for neural networks of the form:

$$f\left(x\right) = \max\left(0, \min\left(1,\frac{\left(x+1\right)}{2}\right)\right)$$

Image Source: [Rinat Maksutov](https://towardsdatascience.com/deep-study-of-a-not-very-deep-neural-network-part-2-activation-functions-fd9bd8d406fc)
BinaryConnect: Training Deep Neural Networks with binary weights during propagations
https://paperswithcode.com/paper/binaryconnect-training-deep-neural-networks
BinaryConnect: Training Deep Neural Networks with binary weights during propagations