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Property testers are fast, randomized "election polling"-type algorithms that determine if an input (e.g., graph or hypergraph) has a certain property or is $\varepsilon$-far from the property. In the dense graph model of property testing,…

Data Structures and Algorithms · Computer Science 2025-08-26 Lior Gishboliner , Asaf Shapira

We initiate a study of a new model of property testing that is a hybrid of testing properties of distributions and testing properties of strings. Specifically, the new model refers to testing properties of distributions, but these are…

Data Structures and Algorithms · Computer Science 2024-02-14 Oded Goldreich , Dana Ron

We initiate a systematic study of the computational complexity of property testing, focusing on the relationship between query and time complexity. While traditional work in property testing has emphasized query complexity, relatively…

Computational Complexity · Computer Science 2026-03-12 Renato Ferreira Pinto , Diptaksho Palit , Sofya Raskhodnikova

Property testing algorithms are highly efficient algorithms, that come with probabilistic accuracy guarantees. For a property P, the goal is to distinguish inputs that have P from those that are far from having P with high probability…

Logic in Computer Science · Computer Science 2020-09-17 Isolde Adler , Polly Fahey

The primary problem in property testing is to decide whether a given function satisfies a certain property, or is far from any function satisfying it. This crucially requires a notion of distance between functions. The most prevalent notion…

Discrete Mathematics · Computer Science 2014-04-04 Deeparnab Chakrabarty , Kashyap Dixit , Madhav Jha , C. Seshadhri

The field of property testing of probability distributions, or distribution testing, aims to provide fast and (most likely) correct answers to questions pertaining to specific aspects of very large datasets. In this work, we consider a…

Data Structures and Algorithms · Computer Science 2015-04-27 Clément L. Canonne

Given a non-negative $n \times n$ matrix viewed as a set of distances between $n$ points, we consider the property testing problem of deciding if it is a metric. We also consider the same problem for two special classes of metrics, tree…

Discrete Mathematics · Computer Science 2024-11-15 Yiqiao Bao , Sampath Kannan , Erik Waingarten

Property Testing is a formal framework to study the computational power and complexity of sampling from combinatorial objects. A central goal in standard graph property testing is to understand which graph properties are testable with…

Data Structures and Algorithms · Computer Science 2025-09-08 Artur Czumaj , Christian Sohler , Stefan Walzer

Given two testable properties $\mathcal{P}_{1}$ and $\mathcal{P}_{2}$, under what conditions are the union, intersection or set-difference of these two properties also testable? We initiate a systematic study of these basic set-theoretic…

Data Structures and Algorithms · Computer Science 2010-10-26 Victor Chen , Madhu Sudan , Ning Xie

An $\epsilon$-test for any non-trivial property (one for which there are both satisfying inputs and inputs of large distance from the property) should use a number of queries that is at least inversely proportional in $\epsilon$. However,…

Data Structures and Algorithms · Computer Science 2024-04-18 Eldar Fischer

We study unitary property testing, where a quantum algorithm is given query access to a black-box unitary and has to decide whether it satisfies some property. In addition to containing the standard quantum query complexity model (where the…

Quantum Physics · Physics 2022-12-12 Adrian She , Henry Yuen

A language L has a property tester if there exists a probabilistic algorithm that given an input x only asks a small number of bits of x and distinguishes the cases as to whether x is in L and x has large Hamming distance from all y in L.…

Quantum Physics · Physics 2007-05-23 H. Buhrman , L. Fortnow , I. Newman , H. Roehrig

We show that for every hereditary permutation property P and every eps>0, there exists an integer M such that if a permutation p is eps-far from P in the Kendall's tau distance, then a random subpermutation of p of order M has the property…

Discrete Mathematics · Computer Science 2015-03-20 Tereza Klimosova , Daniel Kral

In this paper, we consider several property testing problems and ask how the query complexity depends on the distance parameter $\eps$. We achieve new lower bounds in this setting for the problems of testing whether a function is monotone…

Computational Complexity · Computer Science 2013-08-28 Joshua Brody , Pooya Hatami

Distribution testing is a fundamental statistical task with many applications, but we are interested in a variety of problems where systematic mislabelings of the sample prevent us from applying the existing theory. To apply distribution…

Data Structures and Algorithms · Computer Science 2023-04-05 Renato Ferreira Pinto , Nathaniel Harms

We study the question of testing structured properties (classes) of discrete distributions. Specifically, given sample access to an arbitrary distribution $D$ over $[n]$ and a property $\mathcal{P}$, the goal is to distinguish between…

Data Structures and Algorithms · Computer Science 2016-01-22 Clément L. Canonne , Ilias Diakonikolas , Themis Gouleakis , Ronitt Rubinfeld

In this paper, we study the following question: given a black box performing some unknown quantum measurement on a multi-qudit system, how do we test whether this measurement has certain property or is far away from having this property. We…

Quantum Physics · Physics 2012-05-07 Guoming Wang

Fix a prime $p$ and a positive integer $R$. We study the property testing of functions $\mathbb F_p^n\to[R]$. We say that a property is testable if there exists an oblivious tester for this property with one-sided error and constant query…

Combinatorics · Mathematics 2022-08-24 Jonathan Tidor , Yufei Zhao

The Huge Object model of property testing [Goldreich and Ron, TheoretiCS 23] concerns properties of distributions supported on $\{0,1\}^n$, where $n$ is so large that even reading a single sampled string is unrealistic. Instead, query…

Data Structures and Algorithms · Computer Science 2024-12-04 Sourav Chakraborty , Eldar Fischer , Arijit Ghosh , Amit Levi , Gopinath Mishra , Sayantan Sen

In many statistical applications, the dimension is too large to handle for standard high-dimensional machine learning procedures. This is particularly true for graphical models, where the interpretation of a large graph is difficult and…

Statistics Theory · Mathematics 2024-05-20 Luc Devroye , Gábor Lugosi , Piotr Zwiernik
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