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We analyze the spectral properties of the high-dimensional random geometric graph $G(n, d, p)$, formed by sampling $n$ i.i.d vectors $\{v_i\}_{i=1}^{n}$ uniformly on a $d$-dimensional unit sphere and connecting each pair $\{i,j\}$ whenever…

Probability · Mathematics 2026-02-11 Yifan Cao , Yizhe Zhu

We present a randomized algorithm that computes a constant approximation of a graph's arboricity, using $\tilde{O}(n/\lambda)$ queries to adjacency lists and in the same time bound. Here, $n$ and $\lambda$ denote the number of nodes and the…

Data Structures and Algorithms · Computer Science 2025-12-23 Jiangqi Dai , Mohsen Ghaffari , Julian Portmann

Graphons are limit objects of sequences of graphs and are used to analyze the behavior of large graphs. Recently, graphon signal processing has been developed to study signal processing on large graphs. A major limitation of this approach…

Signal Processing · Electrical Eng. & Systems 2024-03-26 Feng Ji , Xingchao Jian , Wee Peng Tay

We propose to study unweighted graphs of constant distance VC-dimension as a broad generalization of many graph classes for which we can compute the diameter in truly subquadratic-time. In particular for any fixed $H$, the class of…

Data Structures and Algorithms · Computer Science 2019-10-31 Guillaume Ducoffe , Michel Habib , Laurent Viennot

We study finite-sum nonlinear programs with localized variable coupling encoded by a (hyper)graph. We introduce a graph-compliant decomposition framework that brings message passing into continuous optimization in a rigorous, implementable,…

Optimization and Control · Mathematics 2026-01-19 Kuangyu Ding , Marie Maros , Gesualdo Scutari

Motivated by an induced counterpart of treewidth sparsifiers (i.e., sparse subgraphs keeping the treewidth large) provided by the celebrated Grid Minor theorem of Robertson and Seymour [JCTB '86] or by a classic result of Chekuri and…

Combinatorics · Mathematics 2024-05-24 Édouard Bonnet

In 2014, Flynn and the second author bounded the average number of components of the functional graphs of polynomials of fixed degree over a finite field. When the fixed degree was large (relative to the size of the finite field), their…

Dynamical Systems · Mathematics 2018-01-11 Elisa Bellah , Derek Garton , Erin Tannenbaum , Noah Walton

The girth of a graph is the length of its shortest cycle. Due to its relevance in graph theory, network analysis and practical fields such as distributed computing, girth-related problems have been object of attention in both past and…

Data Structures and Algorithms · Computer Science 2018-09-21 Kazuhiro Kurita , Kunihiro Wasa , Alessio Conte , Hiroki Arimura , Takeaki Uno

We study the problem of computing the diameter and the mean distance of a continuous graph, i.e., a connected graph where all points along the edges, instead of only the vertices, must be taken into account. It is known that for continuous…

Computational Geometry · Computer Science 2025-03-12 Sergio Cabello , Delia Garijo , Antonia Kalb , Fabian Klute , Irene Parada , Rodrigo I. Silveira

The colored neighborhood metric for sparse graphs was introduced by Bollob\'as and Riordan. The corresponding convergence notion refines a convergence notion introduced by Benjamini and Schramm. We prove that even in this refined sense, the…

Combinatorics · Mathematics 2013-08-23 Hamed Hatami , László Lovász , Balázs Szegedy

Half graphs and their variants, such as ladders, semi-ladders and co-matchings, are combinatorial objects that encode total orders in graphs. Works by Adler and Adler (Eur. J. Comb.; 2014) and Fabia\'nski et al. (STACS; 2019) prove that in…

Combinatorics · Mathematics 2021-03-11 Marek Sokołowski

Merge-width is a recently introduced family of graph parameters that unifies treewidth, clique-width, twin-width, and generalised colouring numbers. We prove the equivalence of several alternative definitions of merge-width, thus…

Spectral hypergraph sparsification, a natural generalization of the well-studied spectral sparsification notion on graphs, has been the subject of intensive research in recent years. In this work, we consider spectral hypergraph…

Data Structures and Algorithms · Computer Science 2025-02-04 Gramoz Goranci , Ali Momeni

In modern applications of graphs algorithms, where the graphs of interest are large and dynamic, it is unrealistic to assume that an input representation contains the full information of a graph being studied. Hence, it is desirable to use…

Data Structures and Algorithms · Computer Science 2020-04-14 Nithin Varma , Yuichi Yoshida

A hypergraph is a generalization of a graph, in which a hyperedge can connect multiple vertices, modeling complex relationships involving multiple vertices simultaneously. Hypergraph pattern matching, which is to find all isomorphic…

Databases · Computer Science 2025-12-23 Siwoo Song , Wonseok Shin , Kunsoo Park , Giuseppe F. Italiano , Zhengyi Yang , Wenjie Zhang

With applications in distribution systems and communication networks, the minimum stretch spanning tree problem is to find a spanning tree T of a graph G such that the maximum distance in T between two adjacent vertices is minimized. The…

Combinatorics · Mathematics 2017-12-12 Lan Lin , Yixun Lin

The diameter of a graph is one if its most important parameters, being used in many real-word applications. In particular, the diameter dictates how fast information can spread throughout data and communication networks. Thus, it is a…

Data Structures and Algorithms · Computer Science 2019-02-21 Keerti Choudhary , Omer Gold

An elimination tree of a connected graph $G$ is a rooted tree on the vertices of $G$ obtained by choosing a root $v$ and recursing on the connected components of $G-v$ to obtain the subtrees of $v$. The graph associahedron of $G$ is a…

Data Structures and Algorithms · Computer Science 2026-03-24 Luís Felipe I. Cunha , Ignasi Sau , Uéverton S. Souza , Mario Valencia-Pabon

Hyperbolicity is a graph parameter related to how much a graph resembles a tree with respect to distances. Its computation is challenging as the main approaches consist in scanning all quadruples of the graph or using fast matrix…

Discrete Mathematics · Computer Science 2021-11-23 David Coudert , André Nusser , Laurent Viennot

In high-dimensional linear models, sparsity is often exploited to reduce variability and achieve parsimony. Equi-sparsity, where one assumes that predictors can be aggregated into groups sharing the same effects, is an alternative…

Methodology · Statistics 2025-10-02 Jinwen Fu , Aaron J. Molstad , Hui Zou