Adversarially Robust Training through Structured Gradient Regularization
Authors: Kevin Roth, Aurelien Lucchi, Sebastian Nowozin, Thomas Hofmann | Published: 2018-05-22
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Adversarial Attacks on Neural Networks for Graph Data
Authors: Daniel Zügner, Amir Akbarnejad, Stephan Günnemann | Published: 2018-05-21 | Updated: 2021-12-09
Constructing Unrestricted Adversarial Examples with Generative Models
Authors: Yang Song, Rui Shu, Nate Kushman, Stefano Ermon | Published: 2018-05-21 | Updated: 2018-12-02
Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference
Authors: Ruying Bao, Sihang Liang, Qingcan Wang | Published: 2018-05-21 | Updated: 2018-09-29
Targeted Adversarial Examples for Black Box Audio Systems
Authors: Rohan Taori, Amog Kamsetty, Brenton Chu, Nikita Vemuri | Published: 2018-05-20 | Updated: 2019-08-20
Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks
Authors: Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha | Published: 2018-05-20 | Updated: 2019-10-03
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Authors: Pouya Samangouei, Maya Kabkab, Rama Chellappa | Published: 2018-05-17 | Updated: 2018-05-18
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning
Authors: Tribhuvanesh Orekondy, Seong Joon Oh, Yang Zhang, Bernt Schiele, Mario Fritz | Published: 2018-05-15 | Updated: 2020-09-13
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary
Authors: Byeongho Heo, Minsik Lee, Sangdoo Yun, Jin Young Choi | Published: 2018-05-15 | Updated: 2018-12-14
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing
Authors: Jingyi Wang, Jun Sun, Peixin Zhang, Xinyu Wang | Published: 2018-05-14 | Updated: 2018-05-17