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Despite having high accuracy, neural nets have been shown to be susceptible to adversarial examples, where a small perturbation to an input can cause it to become mislabeled.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 2001
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Nightmare at test time: robust learning by feature deletion
Amir Globerson and Sam Roweis · 2006
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Learning multiple layers of features from tiny images, 2009
Alex Krizhevsky and Geoffrey Hinton · 2009
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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Huan Xu and Shie Mannor · 2012
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Min Lin, Qiang Chen, and Shuicheng Yan · 2013
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Towards deep neural network architectures robust to adversarial examples
S. Gu and L. Rigazio · 2014
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Caffe: Convolutional architecture for fast feature embedding
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell · 2014
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On the number of linear regions of deep neural networks
Guido F. Montúfar, Razvan Pascanu, KyungHyun Cho, and Yoshua Bengio · 2014
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2014
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Visual causal feature learning
K. Chalupka, P. Perona, and F. Eberhardt · 2015
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Analysis of classifers’ robustness to adversarial perturbations
A. Fawzi, O. Fawzi, and P. Frossard · 2015
Cited alongside, same era.
Explaining and harnessing adversarial examples
Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
Anh Nguyen, Jason Yosinski, and Jeff Clune · 2015
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Adversarial manipulation of deep representations
Sara Sabour, Yanshuai Cao, Fartash Faghri, and David J Fleet · 2015
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Uri Shaham, Yutaro Yamada, and Sahand Negahban · 2015
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Exploring the space of adversarial images
Pedro Tabacof and Eduardo Valle · 2015
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Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
Cited alongside, same era.
Learning with a strong adversary
Ruitong Huang, Bing Xu, Dale Schuurmans, and Csaba Szepesvári · 2015
Cited alongside, same era.
Distributional smoothing with virtual adversarial training
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Ken Nakae, and Shin Ishii · 2015
Cited alongside, same era.
Jiashi Feng, Tom Zahavy, Bingyi Kang, Huan Xu, and Shie Mannor · 2016
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Deepfool: a simple and accurate method to fool deep neural networks
Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi, and Pascal Frossard · 2016
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Practical black-box attacks against deep learning systems using adversarial examples
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z Berkay Celik, and Ananthram Swami · 2016
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