Adaptive Group Testing Algorithms to Estimate the Number of Defectives
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Proceedings of Algorithmic Learning Theory, PMLR 83:93110, 2018.
Abstract
We study the problem of estimating the number of defective
items in adaptive Group testing by using a minimum number of queries.
We improve the existing algorithm and prove a lower bound that shows that,
for constant estimation, the number of tests in our algorithm is optimal.
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