A Bayes-Optimal View on Adversarial Examples
Authors: Eitan Richardson, Yair Weiss | Published: 2020-02-20 | Updated: 2021-03-17
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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
Towards Certifiable Adversarial Sample Detection
Authors: Ilia Shumailov, Yiren Zhao, Robert Mullins, Ross Anderson | Published: 2020-02-20
Boosting Adversarial Training with Hypersphere Embedding
Authors: Tianyu Pang, Xiao Yang, Yinpeng Dong, Kun Xu, Jun Zhu, Hang Su | Published: 2020-02-20 | Updated: 2020-11-25
Data Heterogeneity Differential Privacy: From Theory to Algorithm
Authors: Yilin Kang, Jian Li, Yong Liu, Weiping Wang | Published: 2020-02-20 | Updated: 2023-01-28
On Adaptive Attacks to Adversarial Example Defenses
Authors: Florian Tramer, Nicholas Carlini, Wieland Brendel, Aleksander Madry | Published: 2020-02-19 | Updated: 2020-10-23
Variational Encoder-based Reliable Classification
Authors: Chitresh Bhushan, Zhaoyuan Yang, Nurali Virani, Naresh Iyer | Published: 2020-02-19 | Updated: 2020-10-17
Randomized Smoothing of All Shapes and Sizes
Authors: Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya Razenshteyn, Jerry Li | Published: 2020-02-19 | Updated: 2020-07-23
Influence Function based Data Poisoning Attacks to Top-N Recommender Systems
Authors: Minghong Fang, Neil Zhenqiang Gong, Jia Liu | Published: 2020-02-19 | Updated: 2020-05-31
Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks
Authors: Tsubasa Takahashi | Published: 2020-02-19