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Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks.

, , , and . CoRR, (2021)

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Fast Interactive Image Retrieval using large-scale unlabeled data., , and . CoRR, (2018)Dynamic Domains, Dynamic Solutions: DPCore for Continual Test-Time Adaptation., , and . CoRR, (2024)How Robust Are Randomized Smoothing Based Defenses to Data Poisoning?, , , and . CVPR, page 13244-13253. Computer Vision Foundation / IEEE, (2021)A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness., , , , , , and . ECCV (4), volume 13664 of Lecture Notes in Computer Science, page 654-671. Springer, (2022)Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning., , , and . NeurIPS, page 17347-17359. (2021)How Robust are Randomized Smoothing based Defenses to Data Poisoning?, , , and . CoRR, (2020)Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks., , , and . CoRR, (2021)Penalty Method for Inversion-Free Deep Bilevel Optimization., and . ACML, volume 157 of Proceedings of Machine Learning Research, page 347-362. PMLR, (2021)On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization., , , and . WACV, page 3788-3799. IEEE, (2024)OT-VP: Optimal Transport-guided Visual Prompting for Test-Time Adaptation., , and . CoRR, (2024)