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.
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