TL;DR: What are some fancy applications of combinatorial discrepancy theory?
Combinatorial Discrepancy
Consider a set of white balls $\Omega$ and a family $\mathcal{A}$ of subsets of Omega. The task is to find a two-coloring of $\Omega$, such that in every set $A \in \mathcal{A}$ the difference between the number of "red" and "blue" balls is as low as possible.
Mathematically, this problem can be described as minimizing the discrepancy of a set system: Let $\Omega$ be a finite set and let $\mathcal{A}$ be a family of subsets of $\Omega$. The combinatorial discrepancy of $\mathcal{A}$ is defined as \begin{equation} \operatorname{disc}(\mathcal{A})=\min_{\chi: \Omega \mapsto \{-1,1\}} \max_{A \in \mathcal{A}} |\sum_{a \in A}\chi(a)|. \end{equation} It has been shown, that for $|\Omega|=|\mathcal{A}|=n$, $\operatorname{disc}(A) \leq 6\sqrt{n}$ (see Six Standard Deviations Suffice). Finding colorings $\chi$ that minimize the discrepancy is also a topic of current research (see Constructive Algorithms for Discrepancy Minimization).
I have read that combinatorial discrepancy was used in computer science , but not how and where exactly it is used.
Where is combinatorial discrepancy used in CS? What other fields is combinatorial discrepancy used in (apart from coloring balls)?