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List-decodable robust mean estimation and learning mixtures of spherical gaussians., , and . STOC, page 1047-1060. ACM, (2018)Learning geometric concepts with nasty noise., , and . STOC, page 1061-1073. ACM, (2018)Differentially Private Identity and Equivalence Testing of Discrete Distributions., , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 169-178. PMLR, (2018)Learning k-Modal Distributions via Testing., , and . Theory of Computing, (2014)Near-Optimal Closeness Testing of Discrete Histogram Distributions., , and . ICALP, volume 80 of LIPIcs, page 8:1-8:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2017)List-Decodable Mean Estimation in Nearly-PCA Time., , , , and . CoRR, (2020)Bounded Independence Fools Halfspaces., , , , and . SIAM J. Comput., 39 (8): 3441-3462 (2010)SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions., , , and . CoRR, (2024)Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation., , , , and . CoRR, (2021)A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm., , , , and . CoRR, (2023)