Potential adversarial samples for white-box attacks
Authors: Amir Nazemi, Paul Fieguth | Published: 2019-12-13
ロバスト性
Training Provably Robust Models by Polyhedral Envelope Regularization
Authors: Chen Liu, Mathieu Salzmann, Sabine Süsstrunk | Published: 2019-12-10 | Updated: 2021-09-20
Hardening Random Forest Cyber Detectors Against Adversarial Attacks
Authors: Giovanni Apruzzese, Mauro Andreolini, Michele Colajanni, Mirco Marchetti | Published: 2019-12-09
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness
Authors: Adam Noack, Isaac Ahern, Dejing Dou, Boyang Li | Published: 2019-12-07 | Updated: 2020-12-04
Principal Component Properties of Adversarial Samples
Authors: Malhar Jere, Sandro Herbig, Christine Lind, Farinaz Koushanfar | Published: 2019-12-07
Data Poisoning Attacks on Neighborhood-based Recommender Systems
Authors: Liang Chen, Yangjun Xu, Fenfang Xie, Min Huang, Zibin Zheng | Published: 2019-12-01
Adversarial Attack and Defense on Graph Data: A Survey
Authors: Lichao Sun, Yingtong Dou, Carl Yang, Ji Wang, Yixin Liu, Philip S. Yu, Lifang He, Bo Li | Published: 2018-12-26 | Updated: 2022-10-06
PPD: Permutation Phase Defense Against Adversarial Examples in Deep Learning
Authors: Mehdi Jafarnia-Jahromi, Tasmin Chowdhury, Hsin-Tai Wu, Sayandev Mukherjee | Published: 2018-12-25 | Updated: 2020-01-04
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks
Authors: Thomas Brunner, Frederik Diehl, Michael Truong Le, Alois Knoll | Published: 2018-12-24 | Updated: 2019-05-05
Increasing the adversarial robustness and explainability of capsule networks with $γ$-capsules
Authors: David Peer, Sebastian Stabinger, Antonio Rodriguez-Sanchez | Published: 2018-12-23 | Updated: 2019-12-05