Adaptive Data Analysis in a Balanced Adversarial Model. (arXiv:2305.15452v1 [cs.LG])

In adaptive data analysis, a mechanism gets $n$ i.i.d. samples from an
unknown distribution $D$, and is required to provide accurate estimations to a
sequence of adaptively chosen statistical queries with respect to $D$. Hardt
and Ullman (FOCS 2014) and Steinke and Ullman (COLT 2015) showed that in
general, it is computationally hard to answer more than $\Theta(n^2)$ adaptive
queries, assuming the existence of one-way functions.

However, these negative results strongly rely on an adversarial model that
significantly advantages the …

adversarial analysis data data analysis distribution general respect