Small Ball Probabilities for Simple Random Tensors
Probability
2024-04-01 v1 Functional Analysis
Abstract
We study the small ball probability of an order- simple random tensor where are independent random vectors in that are log-concave or have independent coordinates with bounded densities. We show that the probability that the projection of onto an -dimensional subspace falls within an Euclidean ball of length is upper bounded by and also this upper bound is sharp when is small. We also established that a much better estimate holds true for a random subspace.
Keywords
Cite
@article{arxiv.2403.20192,
title = {Small Ball Probabilities for Simple Random Tensors},
author = {Xuehan Hu and Grigoris Paouris},
journal= {arXiv preprint arXiv:2403.20192},
year = {2024}
}