adversarial robustness

Large Margin Deep Networks for Classification NeurIPS 2018 Lightweight Probabilistic Deep Networks CVPR 2018 Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks NeurIPS 2018 Lipschitz regularity of deep neural networks: analysis and efficient estimation NeurIPS 2018 Max-Mahalanobis Linear Discriminant Analysis Networks ICML 2018 On the Robustness of Semantic Segmentation Models to Adversarial Attacks CVPR 2018 Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training ICML 2018 Robust Classification With Convolutional Prototype Learning CVPR 2018 Robustness of classifiers to uniform ℓ_p and Gaussian noise AISTATS 2018 Robustness of Classifiers to Universal Perturbations: A Geometric Perspective ICLR 2018 Scaling provable adversarial defenses NeurIPS 2018 Sparse DNNs with Improved Adversarial Robustness NeurIPS 2018 Towards Deep Learning Models Resistant to Adversarial Attacks ICLR 2018 Towards Fast Computation of Certified Robustness for ReLU Networks ICML 2018 Wasserstein Introspective Neural Networks CVPR 2018 A Closer Look at Memorization in Deep Networks ICML 2017 Certified Defenses for Data Poisoning Attacks NeurIPS 2017 Efficient Techniques for Crowdsourced Top-k Lists IJCAI 2017 Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation NeurIPS 2017 Minimizing Trust Leaks for Robust Sybil Detection ICML 2017 Learning Communities in the Presence of Errors COLT 2016 Robustness of classifiers: from adversarial to random noise NeurIPS 2016 Clustering Oligarchies AISTATS 2013 Reinforcement Learning in Robust Markov Decision Processes NeurIPS 2013 Robust Sparse Regression under Adversarial Corruption ICML 2013