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Smoothing classifiers and probability density functions with Gaussian kernels appear unrelated, but in this work, they are unified for the problem of robust classification.
On the problem of the most efficient tests of statistical hypotheses
Jerzy Neyman and Egon Sharpe Pearson · 1933
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Abraham Wald · 1945
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An empirical Bayes approach to statistics
Herbert Robbins · 1956
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An empirical Bayes estimator of the mean of a normal population
Koichi Miyasawa · 1961
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On estimation of a probability density function and mode
Emanuel Parzen · 1962
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Vladimir Vapnik · 1992
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Gradient-based learning applied to document recognition
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Information theory, inference and learning algorithms
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Terence Tao · 2012
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Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
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Overfitting or perfect fitting? risk bounds for classification and regression rules that interpolate
Mikhail Belkin, Daniel J Hsu, and Partha Mitra · 2018
Scaling provable adversarial defenses
Eric Wong, Frank Schmidt, Jan Hendrik Metzen, and J Zico Kolter · 2018
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Certified adversarial robustness via randomized smoothing
Jeremy M Cohen, Elan Rosenfeld, and J Zico Kolter · 2019
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Unlabeled data improves adversarial robustness
Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, John C Duchi, and Percy S Liang · 2019
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Rank verification for exponential families
Kenneth Hung, William Fithian, et al · 2019
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Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry · 2019
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Adversarial robustness through local linearization
Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, and Pushmeet Kohli · 2019
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High-dimensional probability: An introduction with applications in data science
Roman Vershynin · 2018
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On approximating ∇ f \nabla f with neural networks
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Provably robust deep learning via adversarially trained smoothed classifiers
Hadi Salman, Greg Yang, Jerry Li, Pengchuan Zhang, Huan Zhang, Ilya Razenshteyn, and Sebastien Bubeck · 2019
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Feature denoising for improving adversarial robustness
Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan L Yuille, and Kaiming He · 2019
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Curse of dimensionality on randomized smoothing for certifiable robustness
Aounon Kumar, Alexander Levine, Tom Goldstein, and Soheil Feizi · 2020
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