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What is Learnable in Valiant's Theory of the Learnable? 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Gaussian Approximations for Maxima of Random Vectors under $(2+ι)$-th Moments
Qiang Sun · 2019-05-27 · via math.ST updates on arXiv.org

We derive a Gaussian approximation result for the maximum of a sum of random vectors under $(2+ι)$-th moments. Our main theorem is abstract and nonasymptotic, and can be applied to a variety of statistical learning problems. The proof uses the Lindeberg telescopic sum device along with some other newly developed technical results.

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