  In an interesting recent work, Kuzborskij and Szepesv\'ari derived a
confidence bound for functions of independent random variables, which is based
on an inequality that relates concentration to squared perturbations of the
chosen function. Kuzborskij and Szepesv\'ari also established the
PAC-Bayes-ification of their confidence bound. Two important aspects of their
work are that the random variables could be of unbounded range, and not
necessarily of an identical distribution. The purpose of this note is to
advertise/discuss these interesting results, with streamlined proofs. This
expository note is written for persons who, metaphorically speaking, enjoy the
"featured movie" but prefer to skip the preview sequence.
