A Research Agenda: Dynamic Models to Defend Against Correlated Attacks
Authors: Ian Goodfellow | Published: 2019-03-14
モデルの頑健性保証
Attribution-driven Causal Analysis for Detection of Adversarial Examples
Authors: Susmit Jha, Sunny Raj, Steven Lawrence Fernandes, Sumit Kumar Jha, Somesh Jha, Gunjan Verma, Brian Jalaian, Ananthram Swami | Published: 2019-03-14
Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models
Authors: Adith Boloor, Xin He, Christopher Gill, Yevgeniy Vorobeychik, Xuan Zhang | Published: 2019-03-12
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier
Authors: Guanxiong Liu, Issa Khalil, Abdallah Khreishah | Published: 2019-03-06
Adversarial Examples on Graph Data: Deep Insights into Attack and Defense
Authors: Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu | Published: 2019-03-05 | Updated: 2019-05-22
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN
Authors: Ke Sun, Zhanxing Zhu, Zhouchen Lin | Published: 2019-02-28
Tensor Dropout for Robust Learning
Authors: Arinbjörn Kolbeinsson, Jean Kossaifi, Yannis Panagakis, Adrian Bulat, Anima Anandkumar, Ioanna Tzoulaki, Paul Matthews | Published: 2019-02-27 | Updated: 2020-12-11
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Authors: Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang | Published: 2019-02-23 | Updated: 2020-01-10
Quantifying Perceptual Distortion of Adversarial Examples
Authors: Matt Jordan, Naren Manoj, Surbhi Goel, Alexandros G. Dimakis | Published: 2019-02-21
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
Authors: Eric Wong, Frank R. Schmidt, J. Zico Kolter | Published: 2019-02-21 | Updated: 2020-01-18