Homogeneous Linear Inequality Constraints for Neural Network Activations

We propose a method to impose homogeneous linear inequality constraints of the form $Ax\leq 0$ on neural network activations. The proposed method allows a data-driven training approach to be combined with modeling prior knowledge about the task... (read more)

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