Revisiting Ensembles in an Adversarial Context: Improving Natural Accuracy
Authors: Aditya Saligrama, Guillaume Leclerc | Published: 2020-02-26
ロバスト性評価
Towards Backdoor Attacks and Defense in Robust Machine Learning Models
Authors: Ezekiel Soremekun, Sakshi Udeshi, Sudipta Chattopadhyay | Published: 2020-02-25 | Updated: 2023-01-11
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
HYDRA: Pruning Adversarially Robust Neural Networks
Authors: Vikash Sehwag, Shiqi Wang, Prateek Mittal, Suman Jana | Published: 2020-02-24 | Updated: 2020-11-10
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers
Authors: Chen Zhu, Renkun Ni, Ping-yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein | Published: 2020-02-22
Robustness from Simple Classifiers
Authors: Sharon Qian, Dimitris Kalimeris, Gal Kaplun, Yaron Singer | Published: 2020-02-21
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
Authors: Dinghuai Zhang, Mao Ye, Chengyue Gong, Zhanxing Zhu, Qiang Liu | Published: 2020-02-21 | Updated: 2020-10-20
A Bayes-Optimal View on Adversarial Examples
Authors: Eitan Richardson, Yair Weiss | Published: 2020-02-20 | Updated: 2021-03-17
On the Decision Boundaries of Neural Networks: A Tropical Geometry Perspective
Authors: Motasem Alfarra, Adel Bibi, Hasan Hammoud, Mohamed Gaafar, Bernard Ghanem | Published: 2020-02-20 | Updated: 2022-08-22
On Adaptive Attacks to Adversarial Example Defenses
Authors: Florian Tramer, Nicholas Carlini, Wieland Brendel, Aleksander Madry | Published: 2020-02-19 | Updated: 2020-10-23