robust accuracy

Accelerating Adversarial Training on Under-Utilized GPU IJCAI 2025 Adapting to Evolving Adversaries with Regularized Continual Robust Training ICML 2025 Adversarial Robustness via Deformable Convolution with Stochasticity ICML 2025 Bridging the Theoretical Gap in Randomized Smoothing AISTATS 2025 Exploring The Forgetting in Adversarial Training: A Novel Method for Enhancing Robustness ICLR 2025 One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy ICML 2025 On the Robustness of Distributed Machine Learning Against Transfer Attacks AAAI 2025 Scaling and Taming Adversarial Training with Synthetic Data ICCV 2025 Accelerating Adversarially Robust Model Selection for Deep Neural Networks via Racing AAAI 2024 Adversarial Feature Map Pruning for Backdoor ICLR 2024 Error Correction Output Codes for Robust Neural Networks against Weight-errors: A Neural Tangent Kernel Point of View NeurIPS 2024 MimicDiffusion: Purifying Adversarial Perturbation via Mimicking Clean Diffusion Model CVPR 2024 Robust Classification via a Single Diffusion Model ICML 2024 Taxonomy Driven Fast Adversarial Training AAAI 2024 Better Diffusion Models Further Improve Adversarial Training ICML 2023 COLA: Orchestrating Error Coding and Learning for Robust Neural Network Inference Against Hardware Defects ICML 2023 GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks ICML 2023 Unlocking Deterministic Robustness Certification on ImageNet NeurIPS 2023 Why adversarial training can hurt robust accuracy ICLR 2023 CAT: Customized Adversarial Training for Improved Robustness IJCAI 2022 Subspace Adversarial Training CVPR 2022 Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart CVPR 2022 Precise Tradeoffs in Adversarial Training for Linear Regression COLT 2020 Are Labels Required for Improving Adversarial Robustness? NeurIPS 2019