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I'm not sure we're on the same page about what this result practically means, so let me re-state it a few different ways, so that people can draw their own conclusions:

* The von Neumann approach will "appear to be O(1) (constant-time)" for any particular biased coin, but that constant might be big if the coin is very, VERY biased in one direction.

* How can this be true? Every flip reduces the probability you do not have an answer exponentially. The "concentration" around the mean is very sharpe.g., at 275 coin tosses for P(H)=0.5 (the fair case), the probability of not having an answer is smaller than 1 divided by the number of atoms in the known universe. It is technically possible, but I think most people would say that it's "effectively constant time" in the sense that we'd expect the coin to phase-shift through the desk before flipping it 275 times in a row and not getting answer. So it takes 275 flips, it's "constant" time! Interpret it how you like though.

* As you make the coin more and more biased, that "horizon" increases linearly, in that 0.99^1,000 is approximately the same thing as 0.999^10,000. So, an order of magnitude increase in probability requires roughly an order of magnitude increase in the number of flips. This is why it's not useful for the adversarial case, and why adversarial extractors are held apart from normal extractors.

Whether this is a "give me my money back" type thing is for you to decide. I think for most people the claim that you can simulate a fair coin from a biased coin in, effectively, O(1), and that the constant increases in O(n) in the bias, is plainly incredible. :)



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