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We study the problem of testing discrete distributions with a focus on the high probability regime. Specifically, given samples from one or more discrete distributions, a property $\mathcal{P}$, and parameters $0< \epsilon, \delta <1$, we…

Data Structures and Algorithms · Computer Science 2020-09-15 Ilias Diakonikolas , Themis Gouleakis , Daniel M. Kane , John Peebles , Eric Price

We consider the problem of hypothesis testing for discrete distributions. In the standard model, where we have sample access to an underlying distribution $p$, extensive research has established optimal bounds for uniformity testing,…

Machine Learning · Computer Science 2024-12-03 Maryam Aliakbarpour , Piotr Indyk , Ronitt Rubinfeld , Sandeep Silwal

Samplers are the backbone of the implementations of any randomised algorithm. Unfortunately, obtaining an efficient algorithm to test the correctness of samplers is very hard to find. Recently, in a series of works, testers like…

Data Structures and Algorithms · Computer Science 2023-12-19 Rishiraj Bhattacharyya , Sourav Chakraborty , Yash Pote , Uddalok Sarkar , Sayantan Sen

Sparsity is a basic property of real vectors that is exploited in a wide variety of applications. In this work, we describe property testing algorithms for sparsity that observe a low-dimensional projection of the input. We consider two…

Data Structures and Algorithms · Computer Science 2017-09-14 Siddharth Barman , Arnab Bhattacharyya , Suprovat Ghoshal

One of the main challenges in property testing is to characterize those properties that are testable with a constant number of queries. For unordered structures such as graphs and hypergraphs this task has been mostly settled. However, for…

Data Structures and Algorithms · Computer Science 2018-01-31 Omri Ben-Eliezer , Eldar Fischer

In recent years much effort has been concentrated towards achieving polynomial time lower bounds on algorithms for solving various well-known problems. A useful technique for showing such lower bounds is to prove them conditionally based on…

Data Structures and Algorithms · Computer Science 2017-07-26 Isaac Goldstein , Tsvi Kopelowitz , Moshe Lewenstein , Ely Porat

We prove that given a computable metric space and two computable measures, the set of points that have high universal uniform test scores with respect to the first measure will have a lower bound with respect to the second measure. This…

Computational Complexity · Computer Science 2023-08-01 Samuel Epstein

In partial function extension, we are given a partial function consisting of $n$ points from a domain and a function value at each point. Our objective is to determine if this partial function can be extended to a function defined on the…

Data Structures and Algorithms · Computer Science 2018-12-17 Umang Bhaskar , Gunjan Kumar

This paper describes three methods for carrying out non-asymptotic inference on partially identified parameters that are solutions to a class of optimization problems. Applications in which the optimization problems arise include estimation…

Methodology · Statistics 2022-12-02 Joel L. Horowitz , Sokbae Lee

We study distribution testing without direct access to a source of relevant data, but rather to one where only a tiny fraction is relevant. To enable this, we introduce the following verification query model. The goal is to perform a…

Data Structures and Algorithms · Computer Science 2025-09-23 Hadley Black , Christopher Ye

Permutation tests are widely used for statistical hypothesis testing when the sampling distribution of the test statistic under the null hypothesis is analytically intractable or unreliable due to finite sample sizes. One critical challenge…

Computation · Statistics 2023-08-29 Yang Shi , Huining Kang , Ji-Hyun Lee , Hui Jiang

Linearity tests are randomized algorithms which have oracle access to the truth table of some function f, and are supposed to distinguish between linear functions and functions which are far from linear. Linearity tests were first…

Computational Complexity · Computer Science 2008-02-21 Shachar Lovett

Motivated by the fact that input distributions are often unknown in advance, distribution-free property testing considers a setting where the algorithmic task is to accept functions $f : [n] \to \{0,1\}$ with a certain property P and reject…

Computational Complexity · Computer Science 2024-02-19 Hugo Aaronson , Tom Gur , Ninad Rajgopal , Ron D. Rothblum

This paper presents a new method for obtaining small algebras to check the admissibility-equivalently, validity in free algebras-of quasi-identities in a finitely generated quasivariety. Unlike a previous algebraic approach of Metcalfe and…

Imagine being able to ask questions to a black box model such as "Which adversarial examples exist?", "Does a specific attribute have a disproportionate effect on the model's prediction?" or "What kind of predictions could possibly be made…

Machine Learning · Computer Science 2021-05-19 Laurens Devos , Wannes Meert , Jesse Davis

We propose automated techniques for the verification and control of probabilistic real-time systems that are only partially observable. To formally model such systems, we define an extension of probabilistic timed automata in which local…

Logic in Computer Science · Computer Science 2015-06-24 Gethin Norman , David Parker , Xueyi Zou

Given a weighted, ordered query set $Q$ and a partition of $Q$ into classes, we study the problem of computing a minimum-cost decision tree that, given any query $q$ in $Q$, uses equality tests and less-than comparisons to determine the…

Data Structures and Algorithms · Computer Science 2025-01-28 Marek Chrobak , Neal E. Young

The framework of distribution testing is currently ubiquitous in the field of property testing. In this model, the input is a probability distribution accessible via independently drawn samples from an oracle. The testing task is to…

Data Structures and Algorithms · Computer Science 2022-09-22 Sourav Chakraborty , Eldar Fischer , Arijit Ghosh , Gopinath Mishra , Sayantan Sen

In estimating the complexity of objects, in particular of graphs, it is common practice to rely on graph- and information-theoretic measures. Here, using integer sequences with properties such as Borel normality, we explain how these…

Information Theory · Computer Science 2017-07-12 Hector Zenil , Narsis Kiani , Jesper Tegnér

In the real world a graph is often fragmented and distributed across different sites. This highlights the need for evaluating queries on distributed graphs. This paper proposes distributed evaluation algorithms for three classes of queries:…

Databases · Computer Science 2012-08-02 Wenfei Fan , Xin Wang , Yinghui Wu