Adversarial Learning

Online Learning with Feedback Graphs: The True Shape of Regret ICML 2023 On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization AAAI 2023 On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator Loss ACL 2023 On the Exploitability of Instruction Tuning NeurIPS 2023 On the Functional Similarity of Robust and Non-Robust Neural Representations ICML 2023 On the Perils of Cascading Robust Classifiers ICLR 2023 On the Privacy Risks of Algorithmic Recourse AISTATS 2023 On the Robustness of Randomized Ensembles to Adversarial Perturbations ICML 2023 On the Role of Generalization in Transferability of Adversarial Examples UAI 2023 On the Role of Randomization in Adversarially Robust Classification NeurIPS 2023 On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection ACL 2023 On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks NeurIPS 2023 Open-Set Semantic Segmentation for Point Clouds via Adversarial Prototype Framework CVPR 2023 Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning NeurIPS 2023 Origins of Low-Dimensional Adversarial Perturbations AISTATS 2023 Orion: Online Backdoor Sample Detection via Evolution Deviance IJCAI 2023 Outlier Robust Adversarial Training ACML 2023 Out-of-distribution Detection with Implicit Outlier Transformation ICLR 2023 Out-of-distribution Representation Learning for Time Series Classification ICLR 2023 PAC-Bayesian Generalization Bounds for Adversarial Generative Models ICML 2023 PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization NeurIPS 2023 PAC-learning for Strategic Classification JMLR 2023 Painterly Image Harmonization in Dual Domains AAAI 2023 Panoptic-Aware Image-to-Image Translation WACV 2023 ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP NeurIPS 2023