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相关论文: Nonadaptive Noise-Resilient Group Testing with Ord…

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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 such as medical testing, communication protocols, pattern…

信息论 · 计算机科学 2018-10-05 Jonathan Scarlett

Future beyond-5G and 6G systems demand ultra-reliable, low-latency communication with short blocklengths, motivating the development of universal decoding algorithms. Guessing decoding, which infers the noise or codeword candidate in order…

信息论 · 计算机科学 2025-11-24 Qianfan Wang , Jifan Liang , Peihong Yuan , Ken R. Duffy , Muriel Médard , Xiao Ma

The group testing problem consists of determining a sparse subset of defective items from within a larger set of items via a series of tests, where each test outcome indicates whether at least one defective item is included in the test. We…

信息论 · 计算机科学 2026-04-24 Daniel McMorrow , Jonathan Scarlett

Group testing is an approach aimed at identifying up to $d$ defective items among a total of $n$ elements. This is accomplished by examining subsets to determine if at least one defective item is present. In our study, we focus on the…

数据结构与算法 · 计算机科学 2023-07-12 Nader H. Bshouty , Catherine A. Haddad-Zaknoon

In this paper, combinatorial quantitative group testing (QGT) with noisy measurements is studied. The goal of QGT is to detect defective items from a data set of size $n$ with counting measurements, each of which counts the number of…

信息论 · 计算机科学 2022-02-01 Yun-Han Li , I-Hsiang Wang

Property testing has been a major area of research in computer science in the last three decades. By property testing we refer to an ensemble of problems, results and algorithms which enable to deduce global information about some data by…

群论 · 数学 2024-07-01 Michael Chapman , Irit Dinur , Alexander Lubotzky

Non-adaptive group testing involves grouping arbitrary subsets of $n$ items into different pools. Each pool is then tested and defective items are identified. A fundamental question involves minimizing the number of pools required to…

离散数学 · 计算机科学 2011-07-26 Mahdi Cheraghchi , Amin Karbasi , Soheil Mohajer , Venkatesh Saligrama

In Group Testing, the objective is to identify $K$ defective items out of $N$, $K\ll N$, by testing pools of items together and using the least amount of tests possible. Recently, a fast decoding method based on binary splitting (Price and…

信息论 · 计算机科学 2025-01-23 Xiaxin Li , Arya Mazumdar

The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of tests, and is relevant in applications such as medical testing, communication protocols, pattern matching, and…

信息论 · 计算机科学 2019-01-30 Jonathan Scarlett , Volkan Cevher

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 such as medical testing, communication protocols, pattern…

信息论 · 计算机科学 2023-09-19 Jonathan Scarlett , Oliver Johnson

Group testing is a long studied problem in combinatorics: A small set of $r$ ill people should be identified out of the whole ($n$ people) by using only queries (tests) of the form "Does set X contain an ill human?". In this paper we…

数据结构与算法 · 计算机科学 2008-04-29 Ely Porat , Amir Rothschild

Group testing enables the identification of a small subset of defective items within a larger population by performing tests on pools of items rather than on each item individually. Over the years, it has not only attracted attention from…

信息论 · 计算机科学 2026-01-13 Manuel Franco-Vivo

The group testing problem consists of determining a small set of defective items from a larger set of items based on tests on groups of items, and is relevant in applications such as medical testing, communication protocols, pattern…

信息论 · 计算机科学 2020-01-27 Steffen Bondorf , Binbin Chen , Jonathan Scarlett , Haifeng Yu , Yuda Zhao

We consider the problem of non-adaptive group testing of $N$ items out of which $K$ or less items are known to be defective. We propose a testing scheme based on left-and-right-regular sparse-graph codes and a simple iterative decoder. We…

信息论 · 计算机科学 2017-01-27 Avinash Vem , Nagaraj T. Janakiraman , Krishna R. Narayanan

The goal of threshold group testing is to identify up to $d$ defective items among a population of $n$ items, where $d$ is usually much smaller than $n$. A test is positive if it has at least $u$ defective items and negative otherwise. Our…

信息论 · 计算机科学 2019-01-09 Thach V. Bui , Minoru Kuribayashi , Mahdi Cheraghchi , Isao Echizen

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 has numerous practical applications. One of the defining features of group testing is…

信息论 · 计算机科学 2021-11-12 Bernard Teo , Jonathan Scarlett

Modern applications are driving demand for ultra-reliable low-latency communications, rekindling interest in the performance of short, high-rate error correcting codes. To that end, here we introduce a soft-detection variant of Guessing…

信息论 · 计算机科学 2021-06-16 Ken R. Duffy

The original problem of group testing consists in the identification of defective items in a collection, by applying tests on groups of items that detect the presence of at least one defective item in the group. The aim is then to identify…

应用统计 · 统计学 2021-06-10 Emilien Joly , Bastien Mallein

The group testing problem is concerned with identifying a small number $k \sim n^\theta$ for $\theta \in (0,1)$ of infected individuals in a large population of size $n$. At our disposal is a testing procedure that allows us to test groups…

离散数学 · 计算机科学 2019-11-19 Max Hahn-Klimroth , Philipp Loick

In group testing, the goal is to identify a subset of defective items within a larger set of items based on tests whose outcomes indicate whether at least one defective item is present. This problem is relevant in areas such as medical…

信息论 · 计算机科学 2022-10-24 Eric Price , Jonathan Scarlett , Nelvin Tan