For a $\sketchCols$ estimate, denoted $\sketchCols_{est}$, and given the following:
\begin{align*}
&\bMu\text{ is the expectation for the sum of estimates.}\\
&X = \sum_{i = 1}^{\sketchRows}X_i \\
&X_i\text{ is i.i.d. r.v.}\in [0, 1], i \in\sketchRows\\
&X_i = \begin{cases}
0 &\sketchCols_{est} > \bMu\\
1 &\sketchCols_{est}\leq\bMu
\end{cases}\\
&p[X_i = 1] \geq\frac{2}{3}\\
&p[X_i = 0] \leq\frac{1}{3}\\
&\mu = \frac{2}{3}\sketchRows\\
&\epsilon = 0.5
\end{align*}
Because Chebyshev bounds tell us that the probability of a bad row estimate is $\leq\frac{1}{3}$, we set epsilon to the value that, when multiplied to $\mu$, outputs $\frac{1}{3}$. We then derive bounds for $\sketchRows$.
Note, because we are only concerned with the left side of the tail, we can use the generic Chernoff bounds for the left tail,
We are now ready to combine the bounds we have derived for both $\sketchCols$ and $\sketchRows$ to which we will refer to as $\bBnd$ and $\mBnd$ respectively.