adversarial robustness

Learn2Perturb: An End-to-End Feature Perturbation Learning to Improve Adversarial Robustness CVPR 2020 Leveraging BERT with Mixup for Sentence Classification (Student Abstract) AAAI 2020 Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing NeurIPS 2020 Lipschitz-Certifiable Training with a Tight Outer Bound NeurIPS 2020 Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack ICML 2020 MMA Training: Direct Input Space Margin Maximization through Adversarial Training ICLR 2020 Modeling Biological Immunity to Adversarial Examples CVPR 2020 More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models ICML 2020 Multi-way Encoding for Robustness WACV 2020 Neural Belief Reasoner IJCAI 2020 Neural Networks with Recurrent Generative Feedback NeurIPS 2020 On 1/n neural representation and robustness NeurIPS 2020 On Adaptive Attacks to Adversarial Example Defenses NeurIPS 2020 On Isometry Robustness of Deep 3D Point Cloud Models Under Adversarial Attacks CVPR 2020 On Lp-norm Robustness of Ensemble Decision Stumps and Trees ICML 2020 On Robustness of Neural Ordinary Differential Equations ICLR 2020 On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples NeurIPS 2020 On the Trade-off between Adversarial and Backdoor Robustness NeurIPS 2020 Parameterized Rate-Distortion Stochastic Encoder ICML 2020 Proper Network Interpretability Helps Adversarial Robustness in Classification ICML 2020 Provable robustness against all adversarial l_p-perturbations for p≥ 1 ICLR 2020 Proximal Mapping for Deep Regularization NeurIPS 2020 Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup ICML 2020 Randomized Smoothing of All Shapes and Sizes ICML 2020 Random Smoothing Might be Unable to Certify ℓ_∞ Robustness for High-Dimensional Images JMLR 2020