robust classifier

Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs ICML 2025 Adversarial AutoMixup ICLR 2024 Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers NeurIPS 2024 Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness NeurIPS 2023 IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers NeurIPS 2023 RANCER: Non-Axis Aligned Anisotropic Certification With Randomized Smoothing WACV 2023 Single Image Backdoor Inversion via Robust Smoothed Classifiers CVPR 2023 Strategic Classification with Unknown User Manipulations ICML 2023 The Best Defense Is a Good Offense: Adversarial Augmentation Against Adversarial Attacks CVPR 2023 Adversarial Learning from Crowds AAAI 2022 Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them ICML 2022 On Some Fast And Robust Classifiers For High Dimension, Low Sample Size Data AISTATS 2022 Pay attention to your loss : understanding misconceptions about Lipschitz neural networks NeurIPS 2022 A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks NeurIPS 2021 Coping with Label Shift via Distributionally Robust Optimisation ICLR 2021 Mixed Nash Equilibria in the Adversarial Examples Game ICML 2021 Universal Adversarial Training AAAI 2020 Adversarial Defense via Learning to Generate Diverse Attacks ICCV 2019 Adversarial examples from computational constraints ICML 2019 Image Synthesis with a Single (Robust) Classifier NeurIPS 2019 Does Distributionally Robust Supervised Learning Give Robust Classifiers? ICML 2018 Learning with Marginalized Corrupted Features ICML 2013 Second Order Cone Programming Approaches for Handling Missing and Uncertain Data JMLR 2006