2.3k citations · 7.1k across the 22 of their papers we have counts for
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stat.ML2017★ 2.3k cited
Ensemble Adversarial Training: Attacks and Defenses
Florian Tramèr, Alexey Kurakin, Nicolas Papernot +3
Adversarial examples are perturbed inputs designed to fool machine learning models. Adversarial training injects such examples into training data to increase robustness. To scale t…
cs.NE2017★ 533 cited
Large-Scale Evolution of Image Classifiers
Esteban Real, Sherry Moore, Andrew Selle +5
Neural networks have proven effective at solving difficult problems but designing their architectures can be challenging, even for image classification problems alone. Our goal is…