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Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference.

, , , and . ICLR, OpenReview.net, (2020)

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AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks., , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 3292-3303. PMLR, (2020)Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork., , , , and . NeurIPS, (2022)Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition., , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 23446-23458. PMLR, (2022)Safe and Robust Watermark Injection with a Single OoD Image., , , , , and . ICLR, OpenReview.net, (2024)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)Real-Time Rogue ONU Identification with 1D-CNN-Based Optical Spectrum Analysis for Secure PON., , , , , and . OFC, page 1-3. IEEE, (2019)Model Compression with Adversarial Robustness: A Unified Optimization Framework., , , , , and . NeurIPS, page 1283-1294. (2019)Privacy-Preserving Deep Visual Recognition: An Adversarial Learning Framework and A New Dataset., , , , and . CoRR, (2019)Taxonomy of Machine Learning Safety: A Survey and Primer., , , , , and . ACM Comput. Surv., 55 (8): 157:1-157:38 (2023)