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Batch normalization (batch norm) is often used in an attempt to stabilize and accelerate training in deep neural networks.
Estimation of Entropy and Mutual Information
L. Paninski · 2003
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2014
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Explaining and Harnessing Adversarial Examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
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Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Deep Learning and the Information Bottleneck Principle
N. Tishby and N. Zaslavsky · 2015
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A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples
T. Tanay and L. D. Griffin · 2016
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Train longer, generalize better: Closing the generalization gap in large batch training of neural networks
E. Hoffer, I. Hubara, and D. Soudry · 2017
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Adversarial Machine Learning at Scale
A. Kurakin, I. J. Goodfellow, and S. Bengio · 2017
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Opening the Black Box of Deep Neural Networks via Information
R. Shwartz-Ziv and N. Tishby · 2017
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L2 Regularization versus Batch and Weight Normalization
T. van Laarhoven · 2017
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Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
A. Athalye, N. Carlini, and D. Wagner · 2018
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Understanding Batch Normalization
N. Bjorck, C. P. Gomes, B. Selman, and K. Q. Weinberger · 2018
Cited alongside, same era.
Adversarial Training Versus Weight Decay
A. Galloway, T. Tanay, and G. W. Taylor · 2018
Cited alongside, same era.
Adversarial Spheres
J. Gilmer, L. Metz, F. Faghri, S. Schoenholz, M. Raghu, M. Wattenberg, and I. Goodfellow · 2018
Cited alongside, same era.
Towards Deep Learning Models Resistant to Adversarial Attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2018
Cited alongside, same era.
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
B. Recht, R. Roelofs, L. Schmidt, and V. Shankar · 2018
Cited alongside, same era.
How Does Batch Normalization Help Optimization?
AdverTorch v0.1: An Adversarial Robustness Toolbox based on PyTorch
G. W. Ding, L. Wang, and X. Jin · 2019
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Adversarial Examples Are a Natural Consequence of Test Error in Noise
N. Ford, J. Gilmer, and E. D. Cubuk · 2019
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ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
R. Geirhos, P. Rubisch, C. Michaelis, M. Bethge, F. A. Wichmann, and W. Brendel · 2019
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Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
D. Hendrycks and T. Dietterich · 2019
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Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness
J.-H. Jacobsen, J. Behrmann, N. Carlini, F. Tramèr, and N. Papernot · 2019
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S. Santurkar, D. Tsipras, A. Ilyas, and A. Madry · 2018
Cited alongside, same era.
Winner’s Curse? On Pace, Progress, and Empirical Rigor
D. Sculley, J. Snoek, A. Wiltschko, and A. Rahimi · 2018
Cited alongside, same era.
Adversarial Vulnerability of Neural Networks Increases With Input Dimension
C.-J. Simon-Gabriel, Y. Ollivier, L. Bottou, B. Schölkopf, and D. Lopez-Paz · 2018
Cited alongside, same era.
The Implicit Bias of Gradient Descent on Separable Data
D. Soudry, E. Hoffer, M. S. Nacson, and N. Srebro · 2018
Cited alongside, same era.
Is Robustness the Cost of Accuracy? – A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
D. Su, H. Zhang, H. Chen, J. Yi, P.-Y. Chen, and Y. Gao · 2018
Cited alongside, same era.
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
W. Brendel and M. Bethge · 2019
Cited alongside, same era.
L. Schott, J. Rauber, M. Bethge, and W. Brendel · 2019
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REPRESENTATION COMPRESSION AND GENERALIZATION IN DEEP NEURAL NETWORKS
R. Shwartz-Ziv, A. Painsky, and N. Tishby · 2019
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Robustness May Be at Odds with Accuracy
D. Tsipras, S. Santurkar, L. Engstrom, A. Turner, and A. Madry · 2019
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A Mean Field Theory of Batch Normalization
G. Yang, J. Pennington, V. Rao, J. Sohl-Dickstein, and S. S. Schoenholz · 2019
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Three Mechanisms of Weight Decay Regularization
G. Zhang, C. Wang, B. Xu, and R. Grosse · 2019
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Residual Learning Without Normalization via Better Initialization
H. Zhang, Y. N. Dauphin, and T. Ma · 2019
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