High-Dimensional Robust Mean Estimation in Nearly-Linear Time

SODA '19: Symposium on Discrete Algorithms San Diego California January, 2019, pp. 2755-2771, 2019.

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Abstract:

We study the fundamental problem of high-dimensional mean estimation in a robust model where a constant fraction of the samples are adversarially corrupted. Recent work gave the first polynomial time algorithms for this problem with dimension-independent error guarantees for several families of structured distributions. In this work, we ...More

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