Preprint
Near-optimal Sample Complexity Bounds for Robust Learning of Gaussians Mixtures via Compression Schemes
Abstract
We prove that $\tilde{\Theta}(k d^2 / \varepsilon^2)$ samples are necessary
and sufficient for learning a mixture of $k$ Gaussians in $\mathbb{R}^d$, up to
Authors
Ashtiani H; Ben-David S; Harvey N; Liaw C; Mehrabian A; Plan Y
Publication date
October 14, 2017
DOI
10.48550/arxiv.1710.05209
Preprint server
arXiv