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A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points (2212.11221v1)
Published 21 Dec 2022 in math.PR, cs.DS, cs.LG, math.ST, stat.ML, and stat.TH
Abstract: We prove that for $c>0$ a sufficiently small universal constant that a random set of $c d2/\log4(d)$ independent Gaussian random points in $\mathbb{R}d$ lie on a common ellipsoid with high probability. This nearly establishes a conjecture of~\cite{SaundersonCPW12}, within logarithmic factors. The latter conjecture has attracted significant attention over the past decade, due to its connections to machine learning and sum-of-squares lower bounds for certain statistical problems.