2022-06-28-buzun22a.md

title	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
Strong Gaussian Approximation for the Sum of Random Vectors	This paper derives a new strong Gaussian approximation bound for the sum of independent random vectors. The approach relies on the optimal transport theory and yields explicit dependence on the dimension size p and the sample size n. This dependence establishes a new fundamental limit for all practical applications of statistical learning theory. Particularly, based on this bound, we prove approximation in distribution for the maximum norm in a high-dimensional setting (p > n).	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	buzun22a	0	Strong Gaussian Approximation for the Sum of Random Vectors	1693	1715	1693-1715	1693	false	Buzun, Nazar and Shvetsov, Nikolay and Dylov, Dmitry V.	given family Nazar Buzun given family Nikolay Shvetsov given family Dmitry V. Dylov	2022-06-28		Proceedings of Thirty Fifth Conference on Learning Theory	178	inproceedings	date-parts 2022 6 28	https://proceedings.mlr.press/v178/buzun22a/buzun22a.pdf