Selected article for: "algorithmic framework and following section detail algorithmic framework describe"
Author: Junan Zhu; Kristina Rivera; Dror Baron
Title: Noisy Pooled PCR for Virus Testing
  • Document date: 2020_4_11
    • ID: f07zk05y_25
    Snippet: We now have a linear relationship from x to w, and the noiseless measurements vector w, which contains the number of sick patients per measurement, is then processed by a probabilistic channel to yield the noisy measurements vector, y. Our goal is to estimate x from y, A, and statistical information about the channel. Other group testing approaches often perform pooled measurements in a first part, and positives are tested individually in a secon.....
    Document: We now have a linear relationship from x to w, and the noiseless measurements vector w, which contains the number of sick patients per measurement, is then processed by a probabilistic channel to yield the noisy measurements vector, y. Our goal is to estimate x from y, A, and statistical information about the channel. Other group testing approaches often perform pooled measurements in a first part, and positives are tested individually in a second part [3] ; our method can improve both parts by pooling all measurements and accounting for all available information. In the following section, we describe our algorithmic framework in detail.

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