Improving Adversarial Robustness via Promoting Ensemble Diversity
Authors: Tianyu Pang, Kun Xu, Chao Du, Ning Chen, Jun Zhu | Published: 2019-01-25 | Updated: 2019-05-29
モデルの頑健性保証
Sitatapatra: Blocking the Transfer of Adversarial Samples
Authors: Ilia Shumailov, Xitong Gao, Yiren Zhao, Robert Mullins, Ross Anderson, Cheng-Zhong Xu | Published: 2019-01-23 | Updated: 2019-11-21
A Multiversion Programming Inspired Approach to Detecting Audio Adversarial Examples
Authors: Qiang Zeng, Jianhai Su, Chenglong Fu, Golam Kayas, Lannan Luo | Published: 2018-12-26 | Updated: 2019-12-03
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
Designing Adversarially Resilient Classifiers using Resilient Feature Engineering
Authors: Kevin Eykholt, Atul Prakash | Published: 2018-12-17
Trust Region Based Adversarial Attack on Neural Networks
Authors: Zhewei Yao, Amir Gholami, Peng Xu, Kurt Keutzer, Michael Mahoney | Published: 2018-12-16
Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples
Authors: Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar | Published: 2018-12-15
AutoGAN: Robust Classifier Against Adversarial Attacks
Authors: Blerta Lindqvist, Shridatt Sugrim, Rauf Izmailov | Published: 2018-12-08
Deep-RBF Networks Revisited: Robust Classification with Rejection
Authors: Pourya Habib Zadeh, Reshad Hosseini, Suvrit Sra | Published: 2018-12-07
The Limitations of Model Uncertainty in Adversarial Settings
Authors: Kathrin Grosse, David Pfaff, Michael Thomas Smith, Michael Backes | Published: 2018-12-06 | Updated: 2019-11-17