In this note, we establish some bounds on the supremum of certain empirical processes indexed by sets of functions with the same
L2 norm. We present several geometric applications of this result, the most important of which is a sharpening of the
Johnson–
Lindenstrauss embedding
Lemma. Our results apply to a large class of random matrices, as we only require that the matrix entries have a subgaussian tail.