Small Ball Probabilities for Simple Random Tensors

Abstract

We study the small ball probability of an order- simple random tensor X=X(1)·s X() where X(i), 1≤ i≤ are independent random vectors in Rn that are log-concave or have independent coordinates with bounded densities. We show that the probability that the projection of X onto an m-dimensional subspace F falls within an Euclidean ball of length is upper bounded by (-1)!(C(e)) and also this upper bound is sharp when m is small. We also established that a much better estimate holds true for a random subspace.

0

Turn this paper into a full lesson

ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…