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): A mixed strategy to obtain better precision on robustness verifications of feed-forward neural networks with piecewise linear activation functions, achieving better precision than incomplete verifiers and more scalability than complete verifiers.