We prove that to estimate within a constant factor the number of defective items in a non-adaptive group testing algorithm we need at least $\tilde\Omega((\log n)(\log(1/\delta)))$ tests. This solves the open problem posed by Damaschke and Sheikh Muhammad.

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We give the first polynomial-time *non-adaptive* proper learning algorithm of Boolean sparse multivariate polynomial under the uniform distribution. Our algorithm, for $s$-sparse polynomial over $n$ variables, makes $q=(s/\epsilon)^{\gamma(s,\epsilon)}\log n$ queries where $2.66\le \gamma(s,\epsilon)\le 6.922$ and runs in $\tilde O(n)\cdot poly(s,1/\epsilon)$ time. We also show that for any $\epsilon=1/s^{O(1)}$ any non-adaptive ... more >>>