Is there some good references of the method Median of Means Estimator? I can't find the term in Wikipedia, and by searching online, I seem to know the original material raised up the idea Median of Means Estimator is this book, while I can only find the scanned edition of this book, so I can't directly search the keywords, and the content seems doesn't offer more useful information where Median of Means Estimator might be raised.
I mainly want to know one theorem which is related to the Median of means estimator, which I read in this paper(Theorem S1 near Eq. (S13) ) is different from the little things I found online. I stated the theorem below for convenient reference:

Let $X$ be a random variable with variance $\sigma^2$. Then, $K$ independent sample means of size $N=34\sigma^2/\epsilon^2$ suffice to construct a median of means estimator $\hat{\mu}(N,K)$ that obeys $Pr[|\hat{\mu}-\mathbb{E}[X]|\ge\epsilon]\le2e^{-K/2}$ for all $\epsilon > 0$.

So is there some formal statement and proof of this kind of theorem of Median of Means Estimator?

If you carry on just a bit further (remarks to theorem 1), they attest to intentionally picking a less tight bound as a worst case...
You can get a tighter bound from here from Proposition 1,
${\rm Pr}(|\hat{\mu}-\mu| > \epsilon) \leq \exp{\left\{-2K\left(\frac{1}{2}-\frac{\sigma^2}{N \epsilon^2}\right)^2\right\}} \leq 2\exp{\left\{-K/2\right\}} \leq \delta/M$
for finite $\sigma^2$ and for some $K=2\log(2M/\delta)$ for $1 \geq \delta \geq 0$
