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We propose an algorithm to enhance certified robustness of a deep model ensemble by optimally weighting each base model.
Improving adversarial robustness of ensembles with diversity training
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Provable defenses against adversarial examples via the convex outer adversarial polytope
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Scaling provable adversarial defenses
Wong, E., Schmidt, F., Metzen, J. H., and Kolter, J. Z. (2018) · 2018
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Efficient neural network robustness certification with general activation functions
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Fast and effective robustness certification
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Adversarial examples are not easily detected: Bypassing ten detection methods
Carlini, N. and Wagner, D. (2017a)
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Zhang, H., Weng, T.-W., Chen, P.-Y., Hsieh, C.-J., and Daniel, L. (2018) · 2018
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