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The rapid development of derandomization theory, which is a fundamental area in theoretical computer science, has recently led to many surprising applications outside its initial intention. We will review some recent such developments…

Information Theory · Computer Science 2015-03-17 Mahdi Cheraghchi

We study the problem of learning an unknown graph via group queries on node subsets, where each query reports whether at least one edge is present among the queried nodes. In general, learning arbitrary graphs with $n$ nodes and $k$ edges…

Information Theory · Computer Science 2025-11-25 Hoang Ta , Jonathan Scarlett

Many combinatorial problems involve determining whether a universe of $n$ elements contains a witness consisting of $k$ elements which have some specified property. In this paper we investigate the relationship between the decision and…

Data Structures and Algorithms · Computer Science 2018-01-08 Kitty Meeks

We introduce a general framework to design and analyze algorithms for the problem of testing homomorphisms between finite groups in the low-soundness regime. In this regime, we give the first constant-query tests for various families of…

Computational Complexity · Computer Science 2025-09-09 Tushant Mittal , Sourya Roy

We formalize a problem we call combinatorial pair testing (CPT), which has applications to the identification of uncooperative or unproductive participants in pair programming, massively distributed computing, and crowdsourcing…

Data Structures and Algorithms · Computer Science 2013-05-02 David Eppstein , Michael T. Goodrich , Daniel S. Hirschberg

Three important issues are often encountered in Supervised and Semi-Supervised Classification: class-memberships are unreliable for some training units (label noise), a proportion of observations might depart from the main structure of the…

Applications · Statistics 2020-07-02 Andrea Cappozzo , Francesca Greselin , Thomas Brendan Murphy

This work is concerned with the detection of a mixture distribution from a $\mathbb{R}$-valued sample. Given a sample $X_1,\dots,X_n$ and an even density $\phi$, our aim is to detect whether the sample distribution is $\phi(\cdot-\mu)$ for…

Statistics Theory · Mathematics 2016-01-22 Béatrice Laurent , Clément Marteau , Cathy Maugis-Rabusseau

The fundamental task of group testing is to recover a small distinguished subset of items from a large population while efficiently reducing the total number of tests (measurements). The key contribution of this paper is in adopting a new…

Information Theory · Computer Science 2015-03-13 George Kamal Atia , Venkatesh Saligrama

We study finite groups $G$ with elements $g$ such that $\lvert \mathbf{C}_G(g)\rvert = \lvert G:G' \rvert$. (Such elements generalize fixed-point-free automorphisms of finite groups.) We show that these groups have a unique conjugacy class…

Group Theory · Mathematics 2023-05-11 Frieder Ladisch

In a group testing scheme, a set of tests is designed to identify a small number $t$ of defective items that are present among a large number $N$ of items. Each test takes as input a group of items and produces a binary output indicating…

Information Theory · Computer Science 2016-11-17 Arya Mazumdar

Modeling potential alloys requires the exploration of all possible configurations of atoms. Additionally, modeling the thermal properties of materials requires knowledge of the possible ways of displacing the atoms. One solution to finding…

Materials Science · Physics 2017-01-11 Wiley S. Morgan , Gus L. W. Hart , Rodney W. Forcade

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

Many binary classification problems minimize misclassification above (or below) a threshold. We show that instances of ranking problems, accuracy at the top or hypothesis testing may be written in this form. We propose a general framework…

Machine Learning · Computer Science 2020-02-26 Lukáš Adam , Václav Mácha , Václav Šmídl , Tomáš Pevný

Model selection is a strategy aimed at creating accurate and robust models. A key challenge in designing these algorithms is identifying the optimal model for classifying any particular input sample. This paper addresses this challenge and…

Machine Learning · Computer Science 2023-05-22 James Kotary , Vincenzo Di Vito , Ferdinando Fioretto

We survey the application of a relatively new branch of statistical physics--"community detection"-- to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the…

Materials Science · Physics 2017-11-22 Z. Nussinov , P. Ronhovde , Dandan Hu , S. Chakrabarty , M. Sahu , Bo Sun , N. A. Mauro , K. K. Sahu

In this work, we give a novel general approach for distribution testing. We describe two techniques: our first technique gives sample-optimal testers, while our second technique gives matching sample lower bounds. As a consequence, we…

Data Structures and Algorithms · Computer Science 2016-05-10 Ilias Diakonikolas , Daniel M. Kane

Finite difference method and pseudo-spectral method have been widely used in the numerical relativity to solve the Einstein equations. As the third major category method to solve partial differential equations, finite element method is much…

General Relativity and Quantum Cosmology · Physics 2018-05-29 Zhoujian Cao , Pei Fu , Li-Wei Ji , Yinhua Xia

We consider semigroup algorithmic problems in finitely generated metabelian groups. Our paper focuses on three decision problems introduced by Choffrut and Karhum\"{a}ki (2005): the Identity Problem (does a semigroup contain a neutral…

Group Theory · Mathematics 2023-04-26 Ruiwen Dong

The centre of the symmetric group algebra $\mathbb{C}[\mathfrak{S}_n]$ has been used successfully for studying important problems in enumerative combinatorics. These include maps in orientable surfaces and ramified covers of the sphere by…

Combinatorics · Mathematics 2011-08-23 David M. Jackson , Craig A. Sloss

Anomaly detection in large populations is a challenging but highly relevant problem. The problem is essentially a multi-hypothesis problem, with a hypothesis for every division of the systems into normal and anomal systems. The number of…

Machine Learning · Computer Science 2013-09-24 Henrik Ohlsson , Tianshi Chen , Sina Khoshfetrat Pakazad , Lennart Ljung , S. Shankar Sastry
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