# List Decodable Mean Estimation in Nearly Linear Time

@article{Cherapanamjeri2020ListDM,
title={List Decodable Mean Estimation in Nearly Linear Time},
author={Yeshwanth Cherapanamjeri and S. Mohanty and Morris Yau},
journal={2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS)},
year={2020},
pages={141-148}
}
• Published 2020
• Computer Science
• 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS)
Learning from data in the presence of outliers is a fundamental problem in statistics. Until recently, no computationally efficient algorithms were known to compute the mean of a high dimensional distribution under natural assumptions in the presence of even a small fraction of outliers. In this paper, we consider robust statistics in the presence of overwhelming outliers where the majority of the dataset is introduced adversarially. With only an $\alpha < 1/2$ fraction of “in-liers” (clean… Expand
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