Feb. 23, 2024, 5:44 a.m. | Yingru Li

stat.ML updates on arXiv.org arxiv.org

arXiv:2402.14026v1 Announce Type: cross
Abstract: We introduce the first probabilistic framework tailored for sequential random projection, an approach rooted in the challenges of sequential decision-making under uncertainty. The analysis is complicated by the sequential dependence and high-dimensional nature of random variables, a byproduct of the adaptive mechanisms inherent in sequential decision processes. Our work features a novel construction of a stopped process, facilitating the analysis of a sequence of concentration events that are interconnected in a sequential manner. By employing …

abstract analysis arxiv challenges cs.ds cs.it cs.na decision framework making math.it math.na math.pr math.st nature probability processes projection random stat.ml stat.th tools type uncertainty variables work

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