activity
20172023
most citedOn Learning and Testing Decision Tree

3 citations · 3 across the 6 of their papers we have counts for

collaborators

8 papers

cs.DS2023

On Detecting Some Defective Items in Group Testing

Nader H. Bshouty, Catherine A. Haddad-Zaknoon

Group testing is an approach aimed at identifying up to defective items among a total of elements. This is accomplished by examining subsets to determine if at least one de…

cs.IT2021

Heuristic Random Designs for Exact Identification of Defectives Using Single Round Non-adaptive Group Testing and Compressed Sensing

Catherine A. Haddad-Zaaknoon

Among the challenges that the COVID-19 pandemic outbreak revealed is the problem to reduce the number of tests required for identifying the virus carriers in order to contain the v…

cs.DS2021★ 3 cited

On Learning and Testing Decision Tree

Nader H. Bshouty, Catherine A. Haddad-Zaknoon

In this paper, we study learning and testing decision tree of size and depth that are significantly smaller than the number of attributes . Our main result addresses the problem…

cs.IT2020

Optimal Deterministic Group Testing Algorithms to Estimate the Number of Defectives

Nader H. Bshouty, Catherine A. Haddad-Zaknoon

We study the problem of estimating the number of defective items within a pile of elements up to a multiplicative factor of , using deterministic group testing algorit…

cs.IT2020

Optimal Randomized Group Testing Algorithm to Determine the Number of Defectives

Nader H. Bshouty, Catherine A. Haddad-Zaknoon, Raghd Boulos +4

We study the problem of determining exactly the number of defective items in an adaptive Group testing by using a minimum number of tests. We improve the existing algorithm and pro…

cs.LG2019

Bounds for the Number of Tests in Non-Adaptive Randomized Algorithms for Group Testing

Nader H. Bshouty, George Haddad, Catherine A. Haddad-Zaknoon

We study the group testing problem with non-adaptive randomized algorithms. Several models have been discussed in the literature to determine how to randomly choose the tests. For…