Improved Algorithms for Non-adaptive Group Testing with Consecutive Positives. Bui, T. V., Cheraghchi, M., & Nguyen, T. D. In Proceedings of the IEEE International Symposium on Information Theory (ISIT), 2021. Paper Link doi abstract bibtex The goal of group testing is to efficiently identify a few specific items, called positives, in a large population of items via tests. A test is an action on a subset of items that returns positive if the subset contains at least one positive and negative otherwise. In non-adaptive group testing, all tests are independent, can be performed in parallel, and represented as a measurement matrix. In this work, we consider non-adaptive group testing with consecutive positives in which the items are linearly ordered and the positives are consecutive in that order. We present two algorithms for efficiently identifying consecutive positives. In particular, without storing measurement matrices, we can identify up to $d$ consecutive positives with $2 łog_2{\frac{n}{d}} + 2d$ ($4 łog_2{\frac{n}{d}} + 2d$, resp.) tests in $O( łog_2^2{\frac{n}{d}} + d)$ ($O( łog_2{\frac{n}{d}} + d)$, resp.) time. These results significantly improve the state-of-the-art scheme in which it takes $5 łog_2{\frac{n}{d}} + 2d + 21$ tests to identify the positives in $O( \frac{n}{d} łog_2{\frac{n}{d}} + d^2)$ time with the measurement matrices associated with the scheme stored somewhere.
@INPROCEEDINGS{ref:BCN21,
author = {Thach V. Bui and Mahdi Cheraghchi and Thuc
D. Nguyen},
title = {Improved Algorithms for Non-adaptive Group Testing
with Consecutive Positives},
year = 2021,
booktitle = {Proceedings of the {IEEE International Symposium on
Information Theory (ISIT)}},
url_Paper = {https://arxiv.org/abs/2101.11294},
url_Link = {https://ieeexplore.ieee.org/document/9518277},
doi = {10.1109/ISIT45174.2021.9518277},
abstract = {The goal of group testing is to efficiently identify
a few specific items, called positives, in a large
population of items via tests. A test is an action
on a subset of items that returns positive if the
subset contains at least one positive and negative
otherwise. In non-adaptive group testing, all tests
are independent, can be performed in parallel, and
represented as a measurement matrix. In this work,
we consider non-adaptive group testing with
consecutive positives in which the items are
linearly ordered and the positives are consecutive
in that order. We present two algorithms for
efficiently identifying consecutive positives. In
particular, without storing measurement matrices, we
can identify up to $d$ consecutive positives with $2
\log_2{\frac{n}{d}} + 2d$ ($4 \log_2{\frac{n}{d}} +
2d$, resp.) tests in $O( \log_2^2{\frac{n}{d}} + d)$
($O( \log_2{\frac{n}{d}} + d)$, resp.) time. These
results significantly improve the state-of-the-art
scheme in which it takes $5 \log_2{\frac{n}{d}} + 2d
+ 21$ tests to identify the positives in $O(
\frac{n}{d} \log_2{\frac{n}{d}} + d^2)$ time with
the measurement matrices associated with the scheme
stored somewhere. }
}
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