2018
ALT
ALT 2018
Adaptive Group Testing Algorithms to Estimate the Number of Defectives
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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Keyword Pioneer
— defective estimation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio