Adversarial Learning

A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks NeurIPS 2021 Amata: An Annealing Mechanism for Adversarial Training Acceleration AAAI 2021 A Multi-Class Hinge Loss for Conditional GANs WACV 2021 A Mutual Information Regularization for Adversarial Training ACML 2021 An Empirical Study on Adversarial Attack on NMT: Languages and Positions Matter ACL 2021 An Empirical Study on Channel Effects for Synthetic Voice Spoofing Countermeasure Systems Interspeech 2021 A Novel Method to Solve Neural Knapsack Problems ICML 2021 Anti-Backdoor Learning: Training Clean Models on Poisoned Data NeurIPS 2021 A PAC-Bayes Analysis of Adversarial Robustness NeurIPS 2021 APGN: Adversarial and Parameter Generation Networks for Multi-Source Cross-Domain Dependency Parsing EMNLP 2021 APo-VAE: Text Generation in Hyperbolic Space NAACL 2021 Appending Adversarial Frames for Universal Video Attack WACV 2021 Approximation Theory Based Methods for RKHS Bandits ICML 2021 ARCH: Efficient Adversarial Regularized Training with Caching EMNLP 2021 Architectural Adversarial Robustness: The Case for Deep Pursuit CVPR 2021 Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks AAAI 2021 Are Chess Discussions Racist? An Adversarial Hate Speech Data Set (Student Abstract) AAAI 2021 ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity ICLR 2021 A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks NeurIPS 2021 A single gradient step finds adversarial examples on random two-layers neural networks NeurIPS 2021 A Strong Baseline for Query Efficient Attacks in a Black Box Setting EMNLP 2021 A Survey on Universal Adversarial Attack IJCAI 2021 A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger’s Adversarial Attacks ACL 2021 Attacks against Ranking Algorithms with Text Embeddings: A Case Study on Recruitment Algorithms EMNLP 2021 Attribute-Guided Adversarial Training for Robustness to Natural Perturbations AAAI 2021