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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)Image Synthesis with a Single (Robust) Classifier., , , , , и . NeurIPS, стр. 1260-1271. (2019)Adversarial Examples Are Not Bugs, They Are Features., , , , , и . NeurIPS, стр. 125-136. (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)Black-box Adversarial Attacks with Limited Queries and Information., , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 2142-2151. PMLR, (2018)Raising the Cost of Malicious AI-Powered Image Editing., , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 29894-29918. PMLR, (2023)Identifying Statistical Bias in Dataset Replication., , , , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 2922-2932. PMLR, (2020)