A uniform Dvoretzky-Kiefer-Wolfowitz inequality

We show that under minimal assumptions on a class of functions $\mathcal{H}$ defined on a probability space $(\mathcal{X},\mu)$, there is a threshold $\Delta_0$ satisfying the following: for every $\Delta\geq\Delta_0$, with probability at least $1-2\exp(-c\Delta m)$ with respect to $\mu^{\otimes m}$, $$\sup_{h\in\mathcal{H}} \sup_{t\in\mathbb{R}} \left| \mathbb{P}(h(X)\leq t) - \frac{1}{m}\sum_{i=1}^m 1_{(-\infty,t]}(h(X_i)) \right| \leq \sqrt{\Delta};$$ here $X$ is distributed according to $\mu$ and $(X_i)_{i=1}^m$ are independent copies of $X$. The value of $\Delta_0$ is determined by an unexpected complexity parameter of the class $\mathcal{H}$ that captures the set's geometry (Talagrand's $\gamma_1$-functional). The bound, the probability estimate and the value of $\Delta_0$ are all optimal up to a logarithmic factor.