Where Does the Robustness Come from? A Study of the Transformation-based Ensemble Defence
Authors: Chang Liao, Yao Cheng, Chengfang Fang, Jie Shi | Published: 2020-09-28 | Updated: 2020-10-08
Beneficial Perturbations Network for Defending Adversarial Examples
Authors: Shixian Wen, Amanda Rios, Laurent Itti | Published: 2020-09-27 | Updated: 2021-09-13
Differentially Private Adversarial Robustness Through Randomized Perturbations
Authors: Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier | Published: 2020-09-27
Federated Transfer Learning: concept and applications
Authors: Sudipan Saha, Tahir Ahmad | Published: 2020-09-26 | Updated: 2021-03-06
A Systematic Review on Model Watermarking for Neural Networks
Authors: Franziska Boenisch | Published: 2020-09-25 | Updated: 2021-12-08
Adversarial Examples in Deep Learning for Multivariate Time Series Regression
Authors: Gautam Raj Mode, Khaza Anuarul Hoque | Published: 2020-09-24
Improving Query Efficiency of Black-box Adversarial Attack
Authors: Yang Bai, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, Weiwei Guo | Published: 2020-09-24 | Updated: 2020-09-25
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization
Authors: Prashnna Kumar Gyawali, Sandesh Ghimire, Linwei Wang | Published: 2020-09-23
Detection of Iterative Adversarial Attacks via Counter Attack
Authors: Matthias Rottmann, Kira Maag, Mathis Peyron, Natasa Krejic, Hanno Gottschalk | Published: 2020-09-23 | Updated: 2021-03-23
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning
Authors: Swanand Kadhe, Nived Rajaraman, O. Ozan Koyluoglu, Kannan Ramchandran | Published: 2020-09-23