In the noisy population recovery problem of Dvir et al., the goal is to learn
an unknown distribution $f$ on binary strings of length $n$ from noisy samples. For some parameter $\mu \in [0,1]$,
a noisy sample is generated by flipping each coordinate of a sample from $f$ independently with
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