Task: Summarization
Input (English): We present a novel approach for the certification of neural networks against adversarial perturbations which combines scalable overapproximation methods with precise (mixed integer) linear programming. This results in significantly better precision than state-of-the-art verifiers on challenging feedforward and convolutional neural networks with piecewise linear activation functions.
Output (English): Introduces a verifier that obtains improvement on precision of incomplete verifiers and scalability of the complete verifiers using over-parameterization, mixed integer linear programming and linear programming relaxation.