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Adversarially Robust Generalization Requires More Data, , , , and . (2018)cite arxiv:1804.11285Comment: Small changes for biblatex compatibility.Better Approximations for Tree Sparsity in Nearly-Linear Time., , and . SODA, page 2215-2229. SIAM, (2017)Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images., , , , , , and . ICCV, page 2616-2627. IEEE, (2023)A fast approximation algorithm for tree-sparse recovery., , and . ISIT, page 1842-1846. IEEE, (2014)Do ImageNet Classifiers Generalize to ImageNet?, , , and . (2019)cite arxiv:1902.10811.CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation., , , , and . CVPR, page 23171-23181. IEEE, (2023)A Meta-Analysis of Overfitting in Machine Learning., , , , , , and . NeurIPS, page 9175-9185. (2019)A Nearly Optimal and Agnostic Algorithm for Properly Learning a Mixture of k Gaussians, for any Constant k., and . CoRR, (2015)Data Filtering Networks., , , , , and . ICLR, OpenReview.net, (2024)Benchmarking Distribution Shift in Tabular Data with TableShift., , and . NeurIPS, (2023)