$\hat{\mu}(x) = {1 \over |\{i : X_i \in L(x)\}|} \sum_{\{i : X_i \in L(x)\}}Y_i$
It is Equation 4 on pg. 6 at this paper: https://arxiv.org/pdf/1510.04342.pdf
It seems like it is saying take the average of $Y_i$ (from what I already know about regression trees) for all points inside of set $L(x)$, but I don't follow how the bars (|) and colon (:) represent this? It would be helpful to get an English explanation for what it means so that I can be sure I'm understanding it correctly going forward in reading the paper.
The colon can be replaced with "such that." So, $\{i:X_i \in L(x)\}$ would mean the set of all $i$ such that $X_i$ is in $L(x)$.
When the bars $|$ are placed around a set, it almost always means the cardinality of the set, which is nothing but the number of elements contained in that set. In other words, $|A|$ refers to the size of the set $A$. So, $|\{i:X_i \in L(x)\}|$ means number of $i$ that satisfy the condition $X_i \in L(x)$.