Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Authors: Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou | Published: 2020-06-15 | Updated: 2021-02-21
敵対的学習
Weight Poisoning Attacks on Pre-trained Models
Authors: Keita Kurita, Paul Michel, Graham Neubig | Published: 2020-04-14
Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions
Authors: Jon Vadillo, Roberto Santana, Jose A. Lozano | Published: 2020-04-14 | Updated: 2023-01-25
Blind Adversarial Training: Balance Accuracy and Robustness
Authors: Haidong Xie, Xueshuang Xiang, Naijin Liu, Bin Dong | Published: 2020-04-10
Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies
Authors: Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang | Published: 2020-03-02 | Updated: 2020-12-12
Adversarial Perturbations Prevail in the Y-Channel of the YCbCr Color Space
Authors: Camilo Pestana, Naveed Akhtar, Wei Liu, David Glance, Ajmal Mian | Published: 2020-02-25
Practical Fast Gradient Sign Attack against Mammographic Image Classifier
Authors: Ibrahim Yilmaz | Published: 2020-01-27
Ensemble Noise Simulation to Handle Uncertainty about Gradient-based Adversarial Attacks
Authors: Rehana Mahfuz, Rajeev Sahay, Aly El Gamal | Published: 2020-01-26
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks
Authors: Farnaz Behnia, Ali Mirzaeian, Mohammad Sabokrou, Sai Manoj, Tinoosh Mohsenin, Khaled N. Khasawneh, Liang Zhao, Houman Homayoun, Avesta Sasan | Published: 2020-01-16
A simple way to make neural networks robust against diverse image corruptions
Authors: Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel | Published: 2020-01-16 | Updated: 2020-07-22