Abstract:
We consider the problem of noisy group testing where the test results are corrupted by noise with an unknown distribution. We propose an adaptive test plan consisting of ...Show MoreMetadata
Abstract:
We consider the problem of noisy group testing where the test results are corrupted by noise with an unknown distribution. We propose an adaptive test plan consisting of a hierarchy of biased random walks guided by a local sequential test which together lend adaptivity and agnosticism to the unknown noise model. We show that the proposed test plan is order optimal in both the population size and the error rate.
Published in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date of Conference: 06-11 June 2021
Date Added to IEEE Xplore: 13 May 2021
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Department of Electrical and Computer Engineering, Cornell University, USA
Department of Electrical and Computer Engineering, Cornell University, USA
Contents Department of Electrical and Computer Engineering, Cornell University, USA
Department of Electrical and Computer Engineering, Cornell University, USA
