The Curious Case of Adversarially Robust Models: More Data Can Help,
Double Descend, or Hurt Generalization

The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization

25 February 2020

Papers citing "The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization"

17 / 17 papers shown

Title
Efficient Optimization Algorithms for Linear Adversarial Training Antônio H. Ribeiro Thomas B. Schon Dave Zahariah Francis Bach AAML 45 1 0 16 Oct 2024
Investigating the Impact of Model Complexity in Large Language Models Jing Luo Huiyuan Wang Weiran Huang 34 0 0 01 Oct 2024
Recent Advances in Attack and Defense Approaches of Large Language Models Jing Cui Yishi Xu Zhewei Huang Shuchang Zhou Jianbin Jiao Junge Zhang PILM AAML 54 1 0 05 Sep 2024
$H$ -Consistency Guarantees for Regression Anqi Mao M. Mohri Yutao Zhong 33 9 0 28 Mar 2024
CUDA: Convolution-based Unlearnable Datasets Vinu Sankar Sadasivan Mahdi Soltanolkotabi S. Feizi MU 29 25 0 07 Mar 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels Simone Bombari Shayan Kiyani Marco Mondelli AAML 33 10 0 03 Feb 2023
Data Augmentation Alone Can Improve Adversarial Training Lin Li Michael W. Spratling 16 50 0 24 Jan 2023
The Effects of Regularization and Data Augmentation are Class Dependent Randall Balestriero Léon Bottou Yann LeCun 28 94 0 07 Apr 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 29 13 0 22 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Understanding Rare Spurious Correlations in Neural Networks Yao-Yuan Yang Chi-Ning Chou Kamalika Chaudhuri AAML 16 25 0 10 Feb 2022
Post-mortem on a deep learning contest: a Simpson's paradox and the complementary roles of scale metrics versus shape metrics Charles H. Martin Michael W. Mahoney 18 19 0 01 Jun 2021
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard Mahdi Soltanolkotabi AAML 26 62 0 21 Oct 2020
Multiple Descent: Design Your Own Generalization Curve Lin Chen Yifei Min M. Belkin Amin Karbasi DRL 23 61 0 03 Aug 2020
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang AAML 33 222 0 25 Feb 2020
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 191 273 0 03 Dec 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 65 230 0 25 May 2018