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Synthesizing Robust Adversarial Examples., , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 284-293. PMLR, (2018)Implementation Matters in Deep RL: A Case Study on PPO and TRPO., , , , , , и . ICLR, OpenReview.net, (2020)Adversarial Examples Are Not Bugs, They Are Features., , , , , и . NeurIPS, стр. 125-136. (2019)Image Synthesis with a Single (Robust) Classifier., , , , , и . NeurIPS, стр. 1260-1271. (2019)Datamodels: Understanding Predictions with Data and Data with Predictions., , , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 9525-9587. PMLR, (2022)What Makes a Good Fisherman? Linear Regression under Self-Selection Bias., , , и . STOC, стр. 1699-1712. ACM, (2023)Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection., , , , , и . CoRR, (2024)3DB: A Framework for Debugging Computer Vision Models., , , , , , , , , и 2 other автор(ы). CoRR, (2021)Synthesizing Robust Adversarial Examples, , , и . (2017)cite arxiv:1707.07397Comment: ICML 2018.FFCV: Accelerating Training by Removing Data Bottlenecks., , , , , и . CVPR, стр. 12011-12020. IEEE, (2023)