adversarial attack

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning AAAI 2020 Stronger and Faster Wasserstein Adversarial Attacks ICML 2020 Suspicion-Free Adversarial Attacks on Clustering Algorithms AAAI 2020 Synthesizing Action Sequences for Modifying Model Decisions AAAI 2020 T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack EMNLP 2020 TBT: Targeted Neural Network Attack With Bit Trojan CVPR 2020 TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP EMNLP 2020 TextAttack: Lessons learned in designing Python frameworks for NLP EMNLP 2020 The Attacker’s Perspective on Automatic Speaker Verification: An Overview Interspeech 2020 The Autoencoding Variational Autoencoder NeurIPS 2020 Thieves on Sesame Street! Model Extraction of BERT-based APIs ICLR 2020 Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control ICLR 2020 Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes CVPR 2020 Towards Adversarially Robust Knowledge Graph Embeddings AAAI 2020 Towards Large Yet Imperceptible Adversarial Image Perturbations With Perceptual Color Distance CVPR 2020 Towards More Practical Adversarial Attacks on Graph Neural Networks NeurIPS 2020 Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent AAAI 2020 Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks ACML 2020 Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking CVPR 2020 Transferable Perturbations of Deep Feature Distributions ICLR 2020 Undersensitivity in Neural Reading Comprehension EMNLP 2020 Universal Adversarial Attacks on Spoken Language Assessment Systems Interspeech 2020 Universal Adversarial Training AAAI 2020 Universal Physical Camouflage Attacks on Object Detectors CVPR 2020 Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings NeurIPS 2020