Thermometer Encoding: One Hot Way To Resist Adversarial Examples

ICLR 2018 Jacob BuckmanAurko RoyColin RaffelIan Goodfellow

It is well known that it is possible to construct "adversarial examples" for neural networks: inputs which are misclassified by the network yet indistinguishable from true data. We propose a simple modification to standard neural network architectures, thermometer encoding, which significantly increases the robustness of the network to adversarial examples... (read more)

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