Mixture models, robustness, and sum of squares proofs

STOC '18: Symposium on Theory of Computing Los Angeles CA USA June, 2018, pp. 1021-1034, 2018.

Cited by: 58|Views13


We use the Sum of Squares method to develop new efficient algorithms for learning well-separated mixtures of Gaussians and robust mean estimation, both in high dimensions, that substantially improve upon the statistical guarantees achieved by previous efficient algorithms. Our contributions are: Mixture models with separated means: We ...More



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