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The goal of combinatorial group testing is to efficiently identify up to $d$ defective items in a large population of $n$ items, where $d \ll n$. Defective items satisfy certain properties while the remaining items in the population do not.…

Information Theory · Computer Science 2019-04-02 Thach V. Bui , Minoru Kuribayashi , Mahdi Cheraghchi , Isao Echizen

We show that any quantum algorithm searching an ordered list of n elements needs to examine at least 1/12 log n-O(1) of them. Classically, log n queries are both necessary and sufficient. This shows that quantum algorithms can achieve only…

Quantum Physics · Physics 2007-05-23 Andris Ambainis

The Huge Object model is a distribution testing model in which we are given access to independent samples from an unknown distribution over the set of strings $\{0,1\}^n$, but are only allowed to query a few bits from the samples. We…

Data Structures and Algorithms · Computer Science 2024-09-18 Tomer Adar , Eldar Fischer , Amit Levi

In multistage group testing, the tests within the same stage are considered nonadaptive, while those conducted across different stages are adaptive. Specifically, when the pools within the same stage are disjoint, meaning that the entire…

Information Theory · Computer Science 2025-07-10 Guojiang Shao

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…

Information Theory · Computer Science 2017-01-27 Avinash Vem , Nagaraj T. Janakiraman , Krishna R. Narayanan

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…

Information Theory · Computer Science 2021-11-12 Bernard Teo , Jonathan Scarlett

We consider an efficiently decodable non-adaptive group testing (NAGT) problem that meets theoretical bounds. The problem is to find a few specific items (at most $d$) satisfying certain characteristics in a colossal number of $N$ items as…

Information Theory · Computer Science 2017-11-20 Thach V. Bui , Minoru Kuribayashi , Isao Echizen

We consider the \emph{approximate minimum selection} problem in presence of \emph{independent random comparison faults}. This problem asks to select one of the smallest $k$ elements in a linearly-ordered collection of $n$ elements by only…

Data Structures and Algorithms · Computer Science 2020-07-08 Stefano Leucci , Chih-Hung Liu

Sorting is the task of ordering $n$ elements using pairwise comparisons. It is well known that $m=\Theta(n\log n)$ comparisons are both necessary and sufficient when the outcomes of the comparisons are observed with no noise. In this paper,…

Information Theory · Computer Science 2024-07-09 Ziao Wang , Nadim Ghaddar , Banghua Zhu , Lele Wang

We consider the problem of testing whether an unknown and arbitrary set $S \subseteq \mathbb{R}^n$ (given as a black-box membership oracle) is convex, versus $\varepsilon$-far from every convex set, under the standard Gaussian distribution.…

Computational Complexity · Computer Science 2024-10-24 Xi Chen , Anindya De , Shivam Nadimpalli , Rocco A. Servedio , Erik Waingarten

Consider $n$ items, each of which is characterised by one of $d+1$ possible features in $\{0, \ldots, d\}$. We study the inference task of learning these types by queries on subsets, or pools, of the items that only reveal a form of…

Information Theory · Computer Science 2022-02-10 Max Hahn-Klimroth , Noela Müller

In this paper, we study the problem of non-adaptive group testing, in which one seeks to identify which items are defective given a set of suitably-designed tests whose outcomes indicate whether or not at least one defective item was…

Information Theory · Computer Science 2025-09-26 Lan V. Truong , Matthew Aldridge , Jonathan Scarlett

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…

Information Theory · Computer Science 2022-10-24 Eric Price , Jonathan Scarlett , Nelvin Tan

This paper considers the problem of Quantitative Group Testing (QGT) where there are some defective items among a large population of $N$ items. We consider the scenario in which each item is defective with probability $K/N$, independently…

Information Theory · Computer Science 2019-10-16 Esmaeil Karimi , Fatemeh Kazemi , Anoosheh Heidarzadeh , Krishna R. Narayanan , Alex Sprintson

We consider the dihedral hidden subgroup problem as the problem of distinguishing hidden subgroup states. We show that the optimal measurement for solving this problem is the so-called pretty good measurement. We then prove that the success…

Quantum Physics · Physics 2018-08-02 Dave Bacon , Andrew M. Childs , Wim van Dam

This article reviews a class of adaptive group testing procedures that operate under a probabilistic model assumption as follows. Consider a set of $N$ items, where item $i$ has the probability $p$ ($p_i$ in the generalized group testing)…

Methodology · Statistics 2021-02-19 Yaakov Malinovsky , Paul S. Albert

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…

Information Theory · Computer Science 2022-02-01 Yun-Han Li , I-Hsiang Wang

Let $1 \le s < t$, $N \ge 1$ be integers and a complex electronic circuit of size $t$ is said to be an $s$-active, $\; s \ll t$, and can work as a system block if not more than $s$ elements of the circuit are defective. Otherwise, the…

Information Theory · Computer Science 2016-07-05 A. G. D'yachkov , I. V. Vorobyev , N. A. Polyanskii , V. Yu. Shchukin

We consider the problem of estimating the number of distinct elements in a large data set (or, equivalently, the support size of the distribution induced by the data set) from a random sample of its elements. The problem occurs in many…

Machine Learning · Computer Science 2021-06-17 Talya Eden , Piotr Indyk , Shyam Narayanan , Ronitt Rubinfeld , Sandeep Silwal , Tal Wagner

In combinatorial group testing problems Questioner needs to find a defective element $x\in [n]$ by testing subsets of $[n]$. In [18] the authors introduced a new model, where each element knows the answer for those queries that contain it…

Discrete Mathematics · Computer Science 2017-05-25 Dániel Gerbner , Máté Vizer
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