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Privacy-Preserving Deep Visual Recognition: An Adversarial Learning Framework and A New Dataset., , , , and . CoRR, (2019)Troubleshooting image segmentation models with human-in-the-loop., , , and . Mach. Learn., 112 (3): 1033-1051 (March 2023)I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively., , , and . ICLR, OpenReview.net, (2020)Troubleshooting Blind Image Quality Models in the Wild., , , , and . CVPR, page 16256-16265. Computer Vision Foundation / IEEE, (2021)Model Compression with Adversarial Robustness: A Unified Optimization Framework., , , , , and . NeurIPS, page 1283-1294. (2019)Real-Time Rogue ONU Identification with 1D-CNN-Based Optical Spectrum Analysis for Secure PON., , , , , and . OFC, page 1-3. IEEE, (2019)Federated Robustness Propagation: Sharing Adversarial Robustness in Federated Learning., , , and . CoRR, (2021)Taxonomy of Machine Learning Safety: A Survey and Primer., , , , , and . ACM Comput. Surv., 55 (8): 157:1-157:38 (2023)Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset., , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 44 (4): 2126-2139 (2022)Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization., , , and . ICLR, OpenReview.net, (2022)