Group testing: an information theory perspective
The group testing problem concerns discovering a small number of defective items within a
large population by performing tests on pools of items. A test is positive if the pool contains …
large population by performing tests on pools of items. A test is positive if the pool contains …
Optimal group testing
A Coja-Oghlan, O Gebhard… - … on Learning Theory, 2020 - proceedings.mlr.press
In the group testing problem, which goes back to the work of Dorfman (1943), we aim to
identify a small set of $ k\sim n^\theta $ infected individuals out of a population size $ n …
identify a small set of $ k\sim n^\theta $ infected individuals out of a population size $ n …
Statistical and computational phase transitions in group testing
A Coja-Oghlan, O Gebhard… - … on Learning Theory, 2022 - proceedings.mlr.press
We study the group testing problem where the goal is to identify a set of k infected
individuals carrying a rare disease within a population of size n, based on the outcomes of …
individuals carrying a rare disease within a population of size n, based on the outcomes of …
Group testing for connected communities
P Nikolopoulos… - International …, 2021 - proceedings.mlr.press
In this paper, we propose algorithms that leverage a known community structure to make
group testing more efficient. We consider a population organized in disjoint communities …
group testing more efficient. We consider a population organized in disjoint communities …
Group testing for overlapping communities
P Nikolopoulos, SR Srinivasavaradhan… - ICC 2021-IEEE …, 2021 - ieeexplore.ieee.org
In this paper, we propose algorithms that leverage a known community structure to make
group testing more efficient. We consider a population organized in connected communities …
group testing more efficient. We consider a population organized in connected communities …
Community-aware group testing
P Nikolopoulos, SR Srinivasavaradhan… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Group testing is a technique that can reduce the number of tests needed to identify infected
members in a population, by pooling together multiple diagnostic samples. Despite the …
members in a population, by pooling together multiple diagnostic samples. Despite the …
Noisy non-adaptive group testing: A (near-) definite defectives approach
J Scarlett, O Johnson - IEEE Transactions on Information …, 2020 - ieeexplore.ieee.org
The group testing problem consists of determining a small set of defective items from a
larger set of items based on a number of possibly-noisy tests, and is relevant in applications …
larger set of items based on a number of possibly-noisy tests, and is relevant in applications …
Phase transitions in the mini-batch size for sparse and dense two-layer neural networks
R Marino, F Ricci-Tersenghi - Machine Learning: Science and …, 2024 - iopscience.iop.org
The use of mini-batches of data in training artificial neural networks is nowadays very
common. Despite its broad usage, theories explaining quantitatively how large or small the …
common. Despite its broad usage, theories explaining quantitatively how large or small the …
Multi-level group testing with application to one-shot pooled COVID-19 tests
One of the main challenges in containing the Coronoavirus disease 2019 (COVID-19)
pandemic stems from the difficulty in carrying out efficient mass diagnosis over large …
pandemic stems from the difficulty in carrying out efficient mass diagnosis over large …
[HTML][HTML] Group testing with a graph infection spread model
The group testing idea is an efficient infection identification approach based on pooling the
test samples of a group of individuals, which results in identification with less number of tests …
test samples of a group of individuals, which results in identification with less number of tests …