Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks
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Wenbo Guo | Xue Liu | Gang Xiong | Peng Liu | Lin Lin | C. Lee Giles | Xinyu Xing | Qinglong Wang | Alexander G. Ororbia | Alexander Ororbia | Qinglong Wang | Xinyu Xing | Xue Liu | Wenbo Guo | Peng Liu | Lin Lin | Gang Xiong
[1] Daniel Kifer,et al. Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization , 2016, ArXiv.
[2] Shin Ishii,et al. Distributional Smoothing with Virtual Adversarial Training , 2015, ICLR 2016.
[3] Arild Nøkland. Improving Back-Propagation by Adding an Adversarial Gradient , 2015, ArXiv.
[4] David A. Wagner,et al. Defensive Distillation is Not Robust to Adversarial Examples , 2016, ArXiv.
[5] Ananthram Swami,et al. Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks , 2015, 2016 IEEE Symposium on Security and Privacy (SP).
[6] Geoffrey E. Hinton. Learning multiple layers of representation , 2007, Trends in Cognitive Sciences.
[7] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[8] J. Kruskal. Nonmetric multidimensional scaling: A numerical method , 1964 .
[9] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[10] Razvan Pascanu,et al. Malware classification with recurrent networks , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[11] Aswin C. Sankaranarayanan,et al. Compressive Sensing , 2008, Computer Vision, A Reference Guide.
[12] Jack W. Stokes,et al. Large-scale malware classification using random projections and neural networks , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[13] Luca Rigazio,et al. Towards Deep Neural Network Architectures Robust to Adversarial Examples , 2014, ICLR.
[14] Ananthram Swami,et al. The Limitations of Deep Learning in Adversarial Settings , 2015, 2016 IEEE European Symposium on Security and Privacy (EuroS&P).
[15] Pascal Vincent,et al. Contractive Auto-Encoders: Explicit Invariance During Feature Extraction , 2011, ICML.
[16] Dawn Xiaodong Song,et al. Recognizing Functions in Binaries with Neural Networks , 2015, USENIX Security Symposium.
[17] Jason Yosinski,et al. Deep neural networks are easily fooled: High confidence predictions for unrecognizable images , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Dale Schuurmans,et al. Learning with a Strong Adversary , 2015, ArXiv.
[19] Hayit Greenspan,et al. Deep learning with non-medical training used for chest pathology identification , 2015, Medical Imaging.
[20] Quoc V. Le,et al. On optimization methods for deep learning , 2011, ICML.
[21] Yann LeCun,et al. Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers , 2012, ICML.
[22] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[23] Yann LeCun,et al. Dimensionality Reduction by Learning an Invariant Mapping , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[24] Jonathon Shlens,et al. Explaining and Harnessing Adversarial Examples , 2014, ICLR.
[25] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[26] Otmar Scherzer,et al. Handbook of Mathematical Methods in Imaging , 2015, Handbook of Mathematical Methods in Imaging.
[27] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[28] Yann LeCun,et al. The mnist database of handwritten digits , 2005 .
[29] Martin J. Wainwright,et al. Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$ -Balls , 2009, IEEE Transactions on Information Theory.
[30] Yan Xu,et al. Deep learning of feature representation with multiple instance learning for medical image analysis , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[31] S. Vavasis. Nonlinear optimization: complexity issues , 1991 .
[32] C. Eckart,et al. The approximation of one matrix by another of lower rank , 1936 .
[33] Urs A. Muller,et al. Learning long-range vision for autonomous off-road driving , 2009 .
[34] Ian T. Jolliffe,et al. Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.
[35] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[36] Zhenlong Yuan,et al. Droid-Sec: deep learning in android malware detection , 2015, SIGCOMM 2015.
[37] Joan Bruna,et al. Intriguing properties of neural networks , 2013, ICLR.
[38] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .