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Related papers: Shotgun identification on groups

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Mossel and Ross (2019) introduce the shotgun assembly problem for random graphs: what radius $R$ ensures that the random graph $G$ can be uniquely recovered from its list of rooted $R$-neighborhoods, with high probability? Here we consider…

Probability · Mathematics 2025-12-03 Brice Huang , Elchanan Mossel , Nike Sun , Claire Zhang , Leqi Zhou

Suppose that three kinds of quantum systems are given in some unknown states $\ket f^{\otimes N}$, $\ket{g_1}^{\otimes K}$, and $\ket{g_2}^{\otimes K}$, and we want to decide which \textit{template} state $\ket{g_1}$ or $\ket{g_2}$, each…

Quantum Physics · Physics 2009-11-07 Masahide Sasaki , Alberto Carlini

Many forensic genetic trace samples are of too low quality to obtain short tandem repeat (STR) DNA profiles as the nuclear DNA they contain is highly degraded (e.g., telogen hairs). Instead, performing shotgun DNA sequencing of such samples…

Applications · Statistics 2026-03-10 Mikkel Meyer Andersen

In query learning, the goal is to identify an unknown object while minimizing the number of "yes or no" questions (queries) posed about that object. We consider three extensions of this fundamental problem that are motivated by practical…

Machine Learning · Statistics 2009-11-25 Gowtham Bellala , Suresh Bhavnani , Clayton Scott

This paper formalizes a latent variable inference problem we call {\em supervised pattern discovery}, the goal of which is to find sets of observations that belong to a single ``pattern.'' We discuss two versions of the problem and prove…

Machine Learning · Statistics 2014-02-10 Jonathan H. Huggins , Cynthia Rudin

We show that, if $w_1, \ldots , w_6$ are words which are not an identity of any (non-abelian) finite simple group, then $w_1(G)w_2(G) \cdots w_6(G) = G$ for all (non-abelian) finite simple groups $G$. In particular, for every word $w$,…

Group Theory · Mathematics 2021-01-08 Michael Larsen , Aner Shalev , Pham Huu Tiep

Given a positive integer $n$, an unlabeled graph $G$ on $n$ vertices, and a vertex $v$ of $G$, let $N_G(v)$ be the subgraph of $G$ induced by vertices of $G$ of distance at most one from $v$. We show that there are universal constants…

Probability · Mathematics 2023-08-28 Han Huang , Konstantin Tikhomirov

A group law is said to be detectable in power subgroups if, for all coprime $m$ and $n$, a group $G$ satisfies the law if and only if the power subgroups $G^m$ and $G^n$ both satisfy the law. We prove that for all positive integers $c$,…

Group Theory · Mathematics 2021-03-09 Giles Gardam

For large classes of group testing problems, we derive lower bounds for the probability that all significant items are uniquely identified using specially constructed random designs. These bounds allow us to optimize parameters of the…

Statistics Theory · Mathematics 2022-02-17 Jack Noonan , Anatoly Zhigljavsky

This paper gives a method for computing distributions associated with patterns in the state sequence of a hidden Markov model, conditional on observing all or part of the observation sequence. Probabilities are computed for very general…

Methodology · Statistics 2007-12-18 John A. D. Aston , Donald E. K. Martin

The NP-complete Permutation Pattern Matching problem asks whether a permutation P (the pattern) can be matched into a permutation T (the text). A matching is an order-preserving embedding of P into T. In the Generalized Permutation Pattern…

Computational Complexity · Computer Science 2013-01-15 Marie-Louise Bruner , Martin Lackner

Patterns on numerical semigroups are multivariate linear polynomials, and they are said to be admissible if there exists a numerical semigroup such that evaluated at any nonincreasing sequence of elements of the semigroup gives integers…

Number Theory · Mathematics 2012-11-06 Maria Bras-Amorós , Pedro A. García-Sánchez , Albert Vico-Oton

In the Best-$K$ identification problem (Best-$K$-Arm), we are given $N$ stochastic bandit arms with unknown reward distributions. Our goal is to identify the $K$ arms with the largest means with high confidence, by drawing samples from the…

Machine Learning · Computer Science 2017-05-22 Haotian Jiang , Jian Li , Mingda Qiao

We study the problem of detecting an attack on a stochastic cyber-physical system. We aim to treat the problem in its most general form. We start by introducing the notion of asymptotically detectable attacks, as those attacks introducing…

Systems and Control · Electrical Eng. & Systems 2021-03-05 Damián Marelli , Tianju Sui , Minyue Fu , Renquan Lu

The focus of this article is on the detection and classification of patterns based on groupoids. The approach hinges on descriptive proximity of points in a set based on the neighborliness property. This approach lends support to image…

Computer Vision and Pattern Recognition · Computer Science 2016-03-08 Enoch A-iyeh , James F. Peters

In this paper, we study sequential testing problems with \emph{overlapping} hypotheses. We first focus on the simple problem of assessing if the mean $\mu$ of a Gaussian distribution is smaller or larger than a fixed $\epsilon>0$; if…

Statistics Theory · Mathematics 2021-11-19 Aurélien Garivier , Emilie Kaufmann

We consider the problem of community detection in the Stochastic Block Model with a finite number $K$ of communities of sizes linearly growing with the network size $n$. This model consists in a random graph such that each pair of vertices…

Social and Information Networks · Computer Science 2014-12-24 Se-Young Yun , Alexandre Proutiere

We review some basic methodologies from pattern recognition that can be applied to helping solve combinatorial problems in free group theory. We illustrate how this works with recognizing Whitehead minimal words in free groups of rank 2.…

Group Theory · Mathematics 2007-06-13 Robert M. Haralick , Alexei D. Miasnikov , Alexei G. Myasnikov

We study the problem of best-arm identification with fixed confidence in stochastic linear bandits. The objective is to identify the best arm with a given level of certainty while minimizing the sampling budget. We devise a simple algorithm…

Machine Learning · Statistics 2020-06-30 Yassir Jedra , Alexandre Proutiere

Graph Neural Networks (GNNs) have improved unsupervised community detection of clustered nodes due to their ability to encode the dual dimensionality of the connectivity and feature information spaces of graphs. Identifying the latent…

Machine Learning · Computer Science 2023-11-28 William Leeney , Ryan McConville