ReluDiff: Differential Verification of Deep Neural Networks

10 Jan 2020Brandon PaulsenJingbo WangChao Wang

As deep neural networks are increasingly being deployed in practice, their efficiency has become an important issue. While there are compression techniques for reducing the network's size, energy consumption and computational requirement, they only demonstrate empirically that there is no loss of accuracy, but lack formal guarantees of the compressed network, e.g., in the presence of adversarial examples... (read more)

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