Adaptive Group Testing Algorithms to Estimate the Number of Defectives

Nader H. Bshouty, Vivian E. Bshouty-Hurani, George Haddad, Thomas Hashem, Fadi Khoury, Omar Sharafy
Proceedings of Algorithmic Learning Theory, PMLR 83:93-110, 2018.

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.

Cite this Paper

BibTeX
@InProceedings{pmlr-v83-bshouty18a, title = {Adaptive Group Testing Algorithms to Estimate the Number of Defectives}, author = {Bshouty, Nader H. and E. Bshouty-Hurani, Vivian and Haddad, George and Hashem, Thomas and Khoury, Fadi and Sharafy, Omar}, booktitle = {Proceedings of Algorithmic Learning Theory}, pages = {93--110}, year = {2018}, editor = {Janoos, Firdaus and Mohri, Mehryar and Sridharan, Karthik}, volume = {83}, series = {Proceedings of Machine Learning Research}, month = {07--09 Apr}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v83/bshouty18a/bshouty18a.pdf}, url = {https://proceedings.mlr.press/v83/bshouty18a.html}, 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.} }
Endnote
%0 Conference Paper %T Adaptive Group Testing Algorithms to Estimate the Number of Defectives %A Nader H. Bshouty %A Vivian E. Bshouty-Hurani %A George Haddad %A Thomas Hashem %A Fadi Khoury %A Omar Sharafy %B Proceedings of Algorithmic Learning Theory %C Proceedings of Machine Learning Research %D 2018 %E Firdaus Janoos %E Mehryar Mohri %E Karthik Sridharan %F pmlr-v83-bshouty18a %I PMLR %P 93--110 %U https://proceedings.mlr.press/v83/bshouty18a.html %V 83 %X 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.
APA
Bshouty, N.H., E. Bshouty-Hurani, V., Haddad, G., Hashem, T., Khoury, F. & Sharafy, O.. (2018). Adaptive Group Testing Algorithms to Estimate the Number of Defectives. Proceedings of Algorithmic Learning Theory, in Proceedings of Machine Learning Research 83:93-110 Available from https://proceedings.mlr.press/v83/bshouty18a.html.

Related Material