An Efficient Algorithm for Capacity-Approaching Noisy Adaptive Group Testing
An Efficient Algorithm for Capacity-Approaching Noisy Adaptive Group Testing
In this paper, we consider the group testing problem with adaptive test designs and noisy outcomes. We propose a computationally efficient four-stage procedure with components including random binning, identification of bins containing defective items, 1-sparse recovery via channel codes, and a "clean-up" step to correct any errors from the earlier …