Large deviations for high-dimensional random projections of pn-balls

Abstract

The paper provides a description of the large deviation behavior for the Euclidean norm of projections of pn-balls to high-dimensional random subspaces. More precisely, for each integer n≥ 1, let kn∈\1,…,n-1\, E(n) be a uniform random kn-dimensional subspace of Rn and X(n) be a random point that is uniformly distributed in the pn-ball of Rn for some p∈[1,∞]. Then the Euclidean norms \|PE(n)X(n)\|2 of the orthogonal projections are shown to satisfy a large deviation principle as the space dimension n tends to infinity. Its speed and rate function are identified, making thereby visible how they depend on p and the growth of the sequence of subspace dimensions kn. As a key tool we prove a probabilistic representation of \|PE(n)X(n)\|2 which allows us to separate the influence of the parameter p and the subspace dimension kn.

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