adversarial robustness

Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions ICML 2020 Recovery of sparse linear classifiers from mixture of responses NeurIPS 2020 Reducing Adversarially Robust Learning to Non-Robust PAC Learning NeurIPS 2020 Regularized Optimal Transport is Ground Cost Adversarial ICML 2020 Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness AAAI 2020 Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks ICML 2020 Reliable Graph Neural Networks via Robust Aggregation NeurIPS 2020 Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness ICLR 2020 Robust Collective Classification against Structural Attacks UAI 2020 Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations NeurIPS 2020 Robust Design of Deep Neural Networks Against Adversarial Attacks Based on Lyapunov Theory CVPR 2020 Robust Encodings: A Framework for Combating Adversarial Typos ACL 2020 Robust Multiple-Path Orienteering Problem: Securing Against Adversarial Attacks RSS 2020 Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation AAAI 2020 Robustness Guarantees for Deep Neural Networks on Videos CVPR 2020 Robustness of Autoencoders for Anomaly Detection Under Adversarial Impact IJCAI 2020 Robustness Verification for Transformers ICLR 2020 Robust Pre-Training by Adversarial Contrastive Learning NeurIPS 2020 SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions ACL 2020 Scalable Differential Privacy with Certified Robustness in Adversarial Learning ICML 2020 Second-Order Provable Defenses against Adversarial Attacks ICML 2020 Security Analysis of Safe and Seldonian Reinforcement Learning Algorithms NeurIPS 2020 Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification ICML 2020 Sign-OPT: A Query-Efficient Hard-label Adversarial Attack ICLR 2020 Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations NeurIPS 2020