It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness

17 March 2023

Papers citing "It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness"

9 / 9 papers shown

Title
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models Alireza Aghabagherloo Aydin Abadi Sumanta Sarkar Vishnu Asutosh Dasu Bart Preneel AAML 50 0 0 01 Apr 2025
Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization Omar Montasser Steve Hanneke Nathan Srebro 16 17 0 15 Sep 2022
The Many Faces of Adversarial Risk Muni Sreenivas Pydi Varun Jog AAML 43 29 0 22 Jan 2022
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal Yucheng Shi Yahong Han Yu-an Tan Xiaohui Kuang 35 26 0 07 Dec 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 45 18 0 07 Oct 2021
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 189 256 0 18 Apr 2021
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization Saehyung Lee Hyungyu Lee Sungroh Yoon AAML 151 113 0 05 Mar 2020
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 60 228 0 25 May 2018
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,102 0 04 Nov 2016