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We prove that any quasirandom uniform hypergraph $H$ can be approximately decomposed into any collection of bounded degree hypergraphs with almost as many edges. In fact, our results also apply to multipartite hypergraphs and even to the…

Combinatorics · Mathematics 2021-01-22 Stefan Ehard , Felix Joos

A variety of information processing tasks in practice involve recovering $n$ objects from single-shot graph-based measurements, particularly those taken over the edges of some measurement graph $\mathcal{G}$. This paper concerns the…

Information Theory · Computer Science 2016-08-04 Yuxin Chen , Andrea J. Goldsmith

In this paper we establish lower bounds on information divergence from a distribution to certain important classes of distributions as Gaussian, exponential, Gamma, Poisson, geometric, and binomial. These lower bounds are tight and for…

Information Theory · Computer Science 2011-02-15 Peter Harremoës , Christophe Vignat

Motivated by applications such as discovering strong ties in social networks and assembling genome subsequences in biology, we study the problem of recovering a hidden $2k$-nearest neighbor (NN) graph in an $n$-vertex complete graph, whose…

Data Structures and Algorithms · Computer Science 2019-11-21 Jian Ding , Yihong Wu , Jiaming Xu , Dana Yang

In this paper we consider the problem of reconstructing a hidden weighted hypergraph of constant rank using additive queries. We prove the following: Let $G$ be a weighted hidden hypergraph of constant rank with n vertices and $m$…

Machine Learning · Computer Science 2010-01-05 Nader H. Bshouty , Hanna Mazzawi

Hypergraph is a data structure that enables us to model higher-order associations among data entities. Conventional graph-structured data can represent pairwise relationships only, whereas hypergraph enables us to associate any number of…

Machine Learning · Computer Science 2024-12-10 Md. Tanvir Alam , Chowdhury Farhan Ahmed , Carson K. Leung

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

This paper studies the problem of recovering a hidden vertex correspondence between two correlated graphs when both edge weights and node features are observed. While most existing work on graph alignment relies primarily on edge…

Statistics Theory · Mathematics 2026-04-07 Dong Huang , Chenyang Tian , Pengkun Yang

We consider the statistical inference problem of recovering an unknown perfect matching, hidden in a weighted random graph, by exploiting the information arising from the use of two different distributions for the weights on the edges…

Disordered Systems and Neural Networks · Physics 2020-08-10 Guilhem Semerjian , Gabriele Sicuro , Lenka Zdeborová

The problems of detecting and recovering planted structures/subgraphs in Erd\H{o}s-R\'{e}nyi random graphs, have received significant attention over the past three decades, leading to many exciting results and mathematical techniques.…

Statistics Theory · Mathematics 2025-05-20 Dor Elimelech , Wasim Huleihel

We consider the problem of detecting a community of densely connected vertices in a high-dimensional bipartite graph of size $n_1 \times n_2$. Under the null hypothesis, the observed graph is drawn from a bipartite Erd\H{o}s-Renyi…

Statistics Theory · Mathematics 2025-05-27 Julien Chhor , Parker Knight

The chain graph model admits both undirected and directed edges in one graph, where symmetric conditional dependencies are encoded via undirected edges and asymmetric causal relations are encoded via directed edges. Though frequently…

Methodology · Statistics 2024-01-29 Ruixuan Zhao , Haoran Zhang , Junhui Wang

In this paper, we consider the graph alignment problem, which is the problem of recovering, given two graphs, a one-to-one mapping between nodes that maximizes edge overlap. This problem can be viewed as a noisy version of the well-known…

Machine Learning · Statistics 2022-01-14 Georgina Hall , Laurent Massoulié

We consider the problem of inferring a matching hidden in a weighted random $k$-hypergraph. We assume that the hyperedges' weights are random and distributed according to two different densities conditioning on the fact that they belong to…

Disordered Systems and Neural Networks · Physics 2022-11-11 Urte Adomaityte , Anshul Toshniwal , Gabriele Sicuro , Lenka Zdeborová

For $n\geq 3$, let $r=r(n)\geq 3$ be an integer. A hypergraph is $r$-uniform if each edge is a set of $r$ vertices, and is said to be linear if two edges intersect in at most one vertex. In this paper, the number of linear $r$-uniform…

Combinatorics · Mathematics 2019-08-20 Brendan D. McKay , Fang Tian

Hypergraph data are often projected onto a weighted graph by constructing an adjacency matrix whose $(i,j)$ entry counts the number of hyperedges containing both nodes $i$ and $j$. This reduction is computationally convenient, but it can…

Statistics Theory · Mathematics 2026-04-20 Kalle Alaluusua , B. R. Vinay Kumar

Among all uniform hypergraphs with even uniformity, the odd-transversal or odd-bipartite hypergraphs are more close to bipartite simple graphs from the viewpoint of both structure and spectrum. A hypergraph is called minimal…

Combinatorics · Mathematics 2021-08-31 Yi-Zheng Fan , Yi Wang , Jiang-Chao Wan

The question whether there exists a hypergraph whose degrees are equal to a given sequence of integers is a well-known reconstruction problem in graph theory, which is motivated by discrete tomography. In this paper we approach the problem…

Combinatorics · Mathematics 2024-02-08 Michela Ascolese , Matthias Lienau , Matthias Schulte , Anusch Taraz

In this paper we present tight lower-bounds and new upper-bounds for hypergraph and database problems. We give tight lower-bounds for finding minimum hypercycles. We give tight lower-bounds for a substantial regime of unweighted hypercycle.…

Computational Complexity · Computer Science 2025-04-29 Cheng-Hao Fu , Andrea Lincoln , Rene Reyes

We consider the problem of detecting a tight community in a sparse random network. This is formalized as testing for the existence of a dense random subgraph in a random graph. Under the null hypothesis, the graph is a realization of an…

Statistics Theory · Mathematics 2014-09-26 Ery Arias-Castro , Nicolas Verzelen
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