DeepAI AI Chat

Adaptive Group Testing Algorithms to Estimate the Number of Defectives

12/02/2017

∙

by Nader H. Bshouty, et al.

∙

∙

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 show that, for constant estimation, the number of tests in our algorithm is optimal.

Nader H. Bshouty
15 publications
Vivian E. Bshouty-Hurani
1 publication
George Haddad
2 publications
Thomas Hashem
1 publication
Fadi Khoury
1 publication
Omar Sharafy
1 publication

page 1

page 2

page 3

page 4

∙ 01/02/2020

Optimal Randomized Group Testing Algorithm to Determine the Number of Defectives

We study the problem of determining exactly the number of defective item...

0 Nader H. Bshouty, et al. ∙

∙ 09/05/2020

Optimal Deterministic Group Testing Algorithms to Estimate the Number of Defectives

We study the problem of estimating the number of defective items d withi...

0 Nader H. Bshouty, et al. ∙

∙ 04/19/2019

Uncertainty about Uncertainty: Near-Optimal Adaptive Algorithms for Estimating Binary Mixtures of Unknown Coins

Given a mixture between two populations of coins, "positive" coins that ...

0 Jasper C. H. Lee, et al. ∙

∙ 02/01/2021

Group Testing in the High Dilution Regime

Non-adaptive group testing refers to the problem of inferring a sparse s...

0 Gabriel Arpino, et al. ∙

∙ 08/27/2021

Group Testing with Non-identical Infection Probabilities

We consider a zero-error probabilistic group testing problem where indiv...

0 Mustafa Doger, et al. ∙

∙ 01/25/2021

On the binary adder channel with complete feedback, with an application to quantitative group testing

We determine the exact value of the optimal symmetric rate point in the ...

0 Samuel H. Florin, et al. ∙

∙ 12/02/2021

Generalized Framework for Group Testing: Queries, Feedbacks and Adversaries

In the Group Testing problem, the objective is to learn a subset K of so...

0 Marek Klonowski, et al. ∙