Sound and Complete Neural Network Repair with Minimality and Locality Guarantees
@article{Fu2021SoundAC, title={Sound and Complete Neural Network Repair with Minimality and Locality Guarantees}, author={Feisi Fu and Wenchao Li}, journal={ArXiv}, year={2021}, volume={abs/2110.07682} }
We present a novel methodology for repairing neural networks that use ReLU activation functions. Unlike existing methods that rely on modifying the weights of a neural network which can induce a global change in the function space, our approach applies only a localized change in the function space while still guaranteeing the removal of the buggy behavior. By leveraging the piecewise linear nature of ReLU networks, our approach can efficiently construct a patch network tailored to the linear…
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