Stochastic Linear Bandits Robust to Adversarial Attacks
Authors: Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett | Published: 2020-07-07 | Updated: 2020-10-27
Robust Learning with Frequency Domain Regularization
Authors: Weiyu Guo, Yidong Ouyang | Published: 2020-07-07
Regional Image Perturbation Reduces $L_p$ Norms of Adversarial Examples While Maintaining Model-to-model Transferability
Authors: Utku Ozbulak, Jonathan Peck, Wesley De Neve, Bart Goossens, Yvan Saeys, Arnout Van Messem | Published: 2020-07-07 | Updated: 2020-07-18
Sharing Models or Coresets: A Study based on Membership Inference Attack
Authors: Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang, Kevin S. Chan | Published: 2020-07-06
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
Authors: Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi | Published: 2020-07-06
Certifying Decision Trees Against Evasion Attacks by Program Analysis
Authors: Stefano Calzavara, Pietro Ferrara, Claudio Lucchese | Published: 2020-07-06
Black-box Adversarial Example Generation with Normalizing Flows
Authors: Hadi M. Dolatabadi, Sarah Erfani, Christopher Leckie | Published: 2020-07-06
On Data Augmentation and Adversarial Risk: An Empirical Analysis
Authors: Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus, Verena Haunschmid, Michal Lewandowski, Werner Zellinger, Bernhard A. Moser, Gerhard Widmer | Published: 2020-07-06
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain
Authors: Ihai Rosenberg, Asaf Shabtai, Yuval Elovici, Lior Rokach | Published: 2020-07-05 | Updated: 2021-03-13
Relationship between manifold smoothness and adversarial vulnerability in deep learning with local errors
Authors: Zijian Jiang, Jianwen Zhou, Haiping Huang | Published: 2020-07-04 | Updated: 2020-12-23