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In this paper we develop a framework to study observability for uniform hypergraphs. Hypergraphs, being extensions of graphs, allow edges to connect multiple nodes and unambiguously represent multi-way relationships which are ubiquitous in…

Dynamical Systems · Mathematics 2023-09-19 Joshua Pickard , Amit Surana , Anthony Bloch , Indika Rajapakse

Distance correlation has become an increasingly popular tool for detecting the nonlinear dependence between a pair of potentially high-dimensional random vectors. Most existing works have explored its asymptotic distributions under the null…

Statistics Theory · Mathematics 2021-10-06 Lan Gao , Yingying Fan , Jinchi Lv , Qi-Man Shao

For any positive edge density $p$, a random graph in the Erd\H{o}s-Renyi $G_{n,p}$ model is connected with non-zero probability, since all edges are mutually independent. We consider random graph models in which edges that do not share…

In this paper we consider a natural extremal graph theoretic problem of topological sort, concerning the minimization of the (topological) connectedness of the independence complex of graphs in terms of its dimension. We observe that the…

Combinatorics · Mathematics 2016-06-21 Penny Haxell , Lothar Narins , Tibor Szabó

Hypergraphs are a generalization of graphs in which edges can connect any number of vertices. They allow the modeling of complex networks with higher-order interactions, and their spectral theory studies the qualitative properties that can…

Combinatorics · Mathematics 2021-12-01 Raffaella Mulas

Testing the equality in distributions of multiple samples is a common task in many fields. However, this problem for high-dimensional or non-Euclidean data has not been well explored. In this paper, we propose new nonparametric tests based…

Methodology · Statistics 2022-05-30 Hoseung Song , Hao Chen

The paper proves the equivalence of the notions of nondeterministic and deterministic parameter testing for uniform dense hypergraphs of arbitrary order. It generalizes the result previously known only for the case of simple graphs. By a…

Data Structures and Algorithms · Computer Science 2015-03-25 Marek Karpinski , Roland Markó

Let $G_1,\dots, G_m$ be independent Bernoulli random subgraphs of the complete graph ${\cal K}_n$ having variable sizes $X_1,\dots, X_m\in \{0,1,2,\dots\}$ and densities $Q_1,\dots, Q_m\in [0,1]$. Letting $n,m\to+\infty$ we establish the…

Probability · Mathematics 2023-11-17 Mindaugas Bloznelis , Dominykas Marma , Rimantas Vaicekauskas

Let the class A of graphs be bridge-addable; that is, whenever a graph G in A has vertices u and v in different components then the graph G+uv is in A. For a random graph sampled uniformly from the graphs in A on vertex set {1,..,n}, there…

Combinatorics · Mathematics 2020-06-04 Colin McDiarmid

We give a probabilistic construction of a $3$-uniform hypergraph on $N$ vertices with independence number $O(\log N / \log \log N)$ in which there are at most two edges among any four vertices. This bound is tight and solves a longstanding…

Combinatorics · Mathematics 2021-03-19 Jacob Fox , Xiaoyu He

We formulate and analyze a novel hypothesis testing problem for inferring the edge structure of an infection graph. In our model, a disease spreads over a network via contagion or random infection, where the random variables governing the…

Statistics Theory · Mathematics 2020-05-05 Justin Khim , Po-Ling Loh

Estimating the probability that the Erd\H{o}s-R\'enyi random graph $G(n,m)$ is $H$-free, for a fixed graph $H$, is one of the fundamental problems in random graph theory. If $m$ is such that each edge of $G(n,m)$ belongs to a copy of $H'$…

Combinatorics · Mathematics 2021-08-13 Rajko Nenadov

We take a different look at the problem of testing the independence of two metric-space-valued random variables using the distance correlation. Instead of testing if the distance correlation vanishes exactly, we are interested in the…

Statistics Theory · Mathematics 2025-11-19 Holger Dette , Marius Kroll

Much data with graph structures satisfy the principle of homophily, meaning that connected nodes tend to be similar with respect to a specific attribute. As such, ubiquitous datasets for graph machine learning tasks have generally been…

Machine Learning · Computer Science 2021-07-07 Derek Lim , Xiuyu Li , Felix Hohne , Ser-Nam Lim

In applications of group testing in networks, e.g. identifying individuals who are infected by a disease spread over a network, exploiting correlation among network nodes provides fundamental opportunities in reducing the number of tests…

Information Theory · Computer Science 2023-03-21 Hesam Nikpey , Jungyeol Kim , Xingran Chen , Saswati Sarkar , Shirin Saeedi Bidokhti

Given two networks of differing sizes, it is of interest to test whether the two networks belong to the same distribution. We formalize the notion of "equality of distribution" under the framework of the generalized random dot product…

Statistics Theory · Mathematics 2026-03-10 Joshua Agterberg , Minh Tang , Carey Priebe

We propose two model-free, permutation-based tests of independence between a pair of random variables. The tests can be applied to samples from any bivariate distribution: continuous, discrete or mixture of those, with light tails or heavy…

Methodology · Statistics 2022-05-16 Jiří Dvořák , Tomáš Mrkvička

One-dimensional geometric random graphs are constructed by distributing $n$ nodes uniformly and independently on a unit interval and then assigning an undirected edge between any two nodes that have a distance at most $r_n$. These graphs…

Physics and Society · Physics 2015-02-20 Jun Zhao , Osman Yağan , Virgil Gligor

In this note we give a new effective proof method for the equivalence of the notions of testability and nondeterministic testability for uniform hypergraph parameters. We provide the first effective upper bound on the sample complexity of…

Data Structures and Algorithms · Computer Science 2015-09-11 Marek Karpinski , Roland Markó

We extend the use of Classification Without Labels for anomaly detection with a hypothesis test designed to exclude the background-only hypothesis. By testing for statistical independence of the two discriminating dataset regions, we are…

High Energy Physics - Phenomenology · Physics 2023-03-16 Jernej F. Kamenik , Manuel Szewc