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Machine learning and deep learning in particular has advanced tremendously on perceptual tasks in recent years.
Learning Multiple Layers of Features from Tiny Images
Alex Krizhevsky · 2009
Earlier work this paper cites.
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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Explaining and Harnessing Adversarial Examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
Earlier work this paper cites.
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe and Christian Szegedy · 2015
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Adam: A Method for Stochastic Optimization
Diederik Kingma and Jimmy Ba · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan and Andrew Zisserman · 2015
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Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, and Zhenyao Zhu · 2016
Cited alongside, same era.
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini and David Wagner · 2016
Cited alongside, same era.
A study of the effect of JPG compression on adversarial images
Gintare Karolina Dziugaite, Zoubin Ghahramani, and Daniel M. Roy · 2016
Cited alongside, same era.
Deep Residual Learning for Image Recognition
Adversarial examples in the physical world
Alexey Kurakin, Ian Goodfellow, and Samy Bengio · 2016
Later among the works it cites.
Are accuracy and robustness correlated?
Andras Rozsa, Terrance E. Boult, and Manuel Gunther · 2016
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A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples
Thomas Tanay and Lewis Griffin · 2016
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Theano: A Python framework for fast computation of mathematical expressions
The Theano Development Team · 2016
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Improving the Robustness of Deep Neural Networks via Stability Training
Stephan Zheng, Yang Song, Thomas Leung, and Ian Goodfellow · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard
Cited in the paper.
DeepFool: A simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, and Pascal Frossard
Cited in the paper.
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
Cited in the paper.
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot, Patrick McDaniel, Xi Wu, Somesh Jha, and Ananthram Swami
Cited in the paper.