Let . The columns of have Euclidean norm at most one. Under the usual sub-Gaussian random vector convention, 3(d) justifies the tuning choice , which is independent of . Also , so the Chernoff bound gives with probability at least .
On the intersection of these events, of probability at least , set and . The weighted Young inequality gives for . Applying it to 3(c) and rearranging yields the rigorous bound
If the coefficient-one concentration statement in 3(d) is taken as an extra hypothesis, instead choose ; the identical argument gives precisely the printed coefficient in the first term. Thus the deterministic argument and its risk rate are sound; its concentration constants depend on correcting or strengthening 3(d).

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