Robust moment estimation and improved clustering via sum of squares
STOC '18: Symposium on Theory of Computing Los Angeles CA USA June, 2018, pp. 1035-1046, 2018.
We develop efficient algorithms for estimating low-degree moments of unknown distributions in the presence of adversarial outliers and design a new family of convex relaxations for k-means clustering based on sum-of-squares method. As an immediate corollary, for any γ > 0, we obtain an efficient algorithm for learning the means of a mixtu...More
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