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.

翻译：Kuzborskij 和 Szepeev\'ari 在最近一项有趣的工作中, Kuzborskij 和 Szepeev\'ari 获得对独立随机变量功能的信任,这种信任基于一种与选定函数的平方扰动有关的不平等。 Kuzborskij 和 Szepesv\'ari 也建立了他们信任的PAC-Bayes化。 他们工作的两个重要方面是随机变量可以不受约束的范围,而不一定是相同的分布。 本说明的目的是用简化的证明来宣传/讨论这些有趣的结果。这个解释性说明是为那些享受“ 特色电影” 的人编写的,但宁愿跳过预览顺序。