Adversarial Examples in Deep Learning: Characterization and Divergence
Authors: Wenqi Wei, Ling Liu, Margaret Loper, Stacey Truex, Lei Yu, Mehmet Emre Gursoy, Yanzhao Wu | Published: 2018-06-29 | Updated: 2018-12-30
Loss Function
Adversarial Regression with Multiple Learners
Authors: Liang Tong, Sixie Yu, Scott Alfeld, Yevgeniy Vorobeychik | Published: 2018-06-06
PAC-learning in the presence of evasion adversaries
Authors: Daniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal | Published: 2018-06-05 | Updated: 2018-06-06
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders
Authors: Partha Ghosh, Arpan Losalka, Michael J Black | Published: 2018-05-31 | Updated: 2018-12-10
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
Authors: Cong Xie, Oluwasanmi Koyejo, Indranil Gupta | Published: 2018-05-25 | Updated: 2019-05-18
Phocas: dimensional Byzantine-resilient stochastic gradient descent
Authors: Cong Xie, Oluwasanmi Koyejo, Indranil Gupta | Published: 2018-05-23
Adversarially Robust Training through Structured Gradient Regularization
Authors: Kevin Roth, Aurelien Lucchi, Sebastian Nowozin, Thomas Hofmann | Published: 2018-05-22
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning
Authors: Jinyuan Jia, Neil Zhenqiang Gong | Published: 2018-05-13 | Updated: 2020-04-13
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
Authors: Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, Bo Li | Published: 2018-04-01 | Updated: 2021-09-28