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Deep neural networks have recently achieved tremendous success in image classification.
Convolutional networks and applications in vision
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Deep learning for healthcare decision making with emrs
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Robustness of classifiers: from adversarial to random noise
A. Fawzi, S.-M. Moosavi-Dezfooli, and P. Frossard · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Delving into transferable adversarial examples and black-box attacks
Y. Liu, X. Chen, C. Liu, and D. Song · 2016
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Deepfool: a simple and accurate method to fool deep neural networks
S.-M. Moosavi-Dezfooli, A. Fawzi, and P. Frossard · 2016
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Simple black-box adversarial perturbations for deep networks
N. Narodytska and S. P. Kasiviswanathan · 2016
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Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models
P.-Y. Chen, H. Zhang, Y. Sharma, J. Yi, and C.-J. Hsieh · 2017
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Houdini: Fooling deep structured prediction models
M. Cisse, Y. Adi, N. Neverova, and J. Keshet · 2017
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Machine learning as an adversarial service: Learning black-box adversarial examples
J. Hayes and G. Danezis · 2017
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Query-efficient black-box adversarial examples
A. Ilyas, L. Engstrom, A. Athalye, and J. Lin · 2017
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Practical black-box attacks against machine learning
N. Papernot, P. McDaniel, I. Goodfellow, S. Jha, Z. B. Celik, and A. Swami · 2017
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Query-efficient black-box attack by active learning
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