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Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries.

, , и . AAAI, стр. 4045-4053. AAAI Press, (2021)

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Marios Pittas

Mary Pittas-Herschbach

 

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The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model., , , и . COLT, том 134 из Proceedings of Machine Learning Research, стр. 1552-1584. PMLR, (2021)Streaming Algorithms for High-Dimensional Robust Statistics., , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 5061-5117. PMLR, (2022)Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression., , , и . CoRR, (2023)Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation., , , и . CoRR, (2023)Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA., , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 7886-7921. PMLR, (2023)SQ Lower Bounds for Learning Bounded Covariance GMMs., , , и . CoRR, (2023)Statistical Query Lower Bounds for Learning Truncated Gaussians., , , и . CoRR, (2024)The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals., , , и . CoRR, (2021)Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries., , и . AAAI, стр. 4045-4053. AAAI Press, (2021)SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians., , , и . COLT, том 195 из Proceedings of Machine Learning Research, стр. 2319-2349. PMLR, (2023)