adversarial attack

The Adversarial Attack and Detection under the Fisher Information Metric AAAI 2019 The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure AAAI 2019 The FEVER2.0 Shared Task EMNLP 2019 The Limitations of Adversarial Training and the Blind-Spot Attack ICLR 2019 The LogBarrier Adversarial Attack: Making Effective Use of Decision Boundary Information ICCV 2019 Theoretical evidence for adversarial robustness through randomization NeurIPS 2019 Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective IJCAI 2019 Transferable Clean-Label Poisoning Attacks on Deep Neural Nets ICML 2019 Trust Region Based Adversarial Attack on Neural Networks CVPR 2019 Universal Adversarial Triggers for Attacking and Analyzing NLP EMNLP 2019 Universal Multi-Party Poisoning Attacks ICML 2019 What Does It Mean to Learn in Deep Networks? And, How Does One Detect Adversarial Attacks? CVPR 2019 White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks NAACL 2019 ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization NeurIPS 2019 Adversarial Attack on Graph Structured Data ICML 2018 Adversarial Attacks on Stochastic Bandits NeurIPS 2018 Adversarial Examples that Fool both Computer Vision and Time-Limited Humans NeurIPS 2018 Analytic Expressions for Probabilistic Moments of PL-DNN With Gaussian Input CVPR 2018 Attacking Binarized Neural Networks ICLR 2018 Attention-Guided Answer Distillation for Machine Reading Comprehension EMNLP 2018 Black-box Adversarial Attacks with Limited Queries and Information ICML 2018 Boosting Adversarial Attacks With Momentum CVPR 2018 Countering Adversarial Images using Input Transformations ICLR 2018 Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models ICLR 2018 Deep Defense: Training DNNs with Improved Adversarial Robustness NeurIPS 2018