Randomization scares me a bit, but one can run several copies at the same time to get a better estimate, I guess. I like how you can easily obtain the granularity of an estimate after stopping, 2^k is increment size after k^th round.

I wonder, what are error distributions and how probable it is to not exceed 2^k of an error, maybe I should read the article, after all 😅

Thank you for an excerpt

Edit: looks like if we have (ε, δ)-approximation if distribution of data, error would be less than δ/4