Heterogeneous Hoeffding/McDiarmid Hoeffding's inequality for independent random variables $a_i\le X_i\le b_i$ states that their sum has sub-Gaussian tails, decaying as $\exp(-2t^2/\sum_i (b_i-a_i)^2)$. Question: Are there any interesting applications exploiting the heterogeneous ranges? In all of the applications I'm aware of, either the $X_i$ all have the same range, or else Hoeffding/McDiarmid (and for that matter, Bernstein/Bennett) are simply too crude, and a sharper tool such as Kearns-Saul is called for (see, e.g., Theorem 1(i) in http://jmlr.org/papers/v16/berend15a.html, or Theorem 2.1 in https://projecteuclid.org/euclid.ecp/1465315542; Talagrand's inequality also comes to mind of course). So again: is heterogenous Hoeffding actually ever used?
Yes. See for example the stronger concentration for the occupancy problem in the following note:

http://sarielhp.org/teach/17/b/lec/10_martin_II.pdf

Theorems 10.3.1 and 10.3.2.
(This is also covered in the Randomized Algorithm book by Motwani and Raghavan).

The version stated here is the martingale version, but it is the same thing...