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Hi I have a doubt at the end of the proof of the RAPPOR Algorithm, when they say the sensitivity is maximized when $b'_{h+1}=b'_{h+2}=...=b'_{2h}=1$ and $b'_{1}=b'_{2}=...=b'_{h}=0$. I don't understand if the maximized is define as the ratio of probabilities or comes from the definitions of sensitivity in differential privacy.
Link Paper: https://static.googleusercontent.com/media/research.google.com/es//pubs/archive/42852.pdf
I will appreciate any help. Thanks.
Sensitivity is normally defined as the maximum change between outputs of a function between neighboring datasets, before noise addition. But in this particular sentence, they seem to use the term to mean "the maximum probability change between outputs, after noise addition". It's not a very typical use of terminology.
