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This paper systematically studies the behavior of the leading eigenvectors for independent edge undirected random graphs generated from a general latent position model whose link function is possibly infinite rank and also possibly…

Statistics Theory · Mathematics 2025-01-28 Minh Tang , Joshua R. Cape

We develop a general embedding method based on the Friedman-Pippenger tree embedding technique (1987) and its algorithmic version, essentially due to Aggarwal et al. (1996), enhanced with a roll-back idea allowing to sequentially retrace…

Combinatorics · Mathematics 2021-03-22 Nemanja Draganić , Michael Krivelevich , Rajko Nenadov

We introduce a method to embed edge-colored graphs into families of expander graphs, which generalizes a framework developed by Dragani\'c, Krivelevich, and Nenadov (2022). As an application, we show that each family of sufficiently…

Combinatorics · Mathematics 2025-01-27 Ben Lund , Chuandong Xu

By definition, a rigid graph in $\mathbb{R}^d$ (or on a sphere) has a finite number of embeddings up to rigid motions for a given set of edge length constraints. These embeddings are related to the real solutions of an algebraic system.…

Combinatorics · Mathematics 2021-10-26 Evangelos Bartzos , Ioannis Z. Emiris , Raimundas Vidunas

We prove improved bounds on how localized an eigenvector of a high girth regular graph can be, and present examples showing that these bounds are close to sharp. This study was initiated by Brooks and Lindenstrauss (2009) who relied on the…

Combinatorics · Mathematics 2021-08-06 Shirshendu Ganguly , Nikhil Srivastava

The celebrated Cheeger's Inequality establishes a bound on the edge expansion of a graph via its spectrum. This inequality is central to a rich spectral theory of graphs, based on studying the eigenvalues and eigenvectors of the adjacency…

Discrete Mathematics · Computer Science 2016-05-06 T-H. Hubert Chan , Anand Louis , Zhihao Gavin Tang , Chenzi Zhang

Many link prediction algorithms require the computation of a similarity metric on each vertex pair, which is quadratic in the number of vertices and infeasible for large networks. We develop a class of link prediction algorithms based on a…

Social and Information Networks · Computer Science 2017-04-10 Benjamin Pachev , Benjamin Webb

In this paper we study variants of the widely used spectral clustering that partitions a graph into k clusters by (1) embedding the vertices of a graph into a low-dimensional space using the bottom eigenvectors of the Laplacian matrix, and…

Data Structures and Algorithms · Computer Science 2017-02-01 Richard Peng , He Sun , Luca Zanetti

We establish an Expander Mixing Lemma for directed graphs in terms of the eigenvalues of an associated asymmetric transition probability matrix, extending the classical spectral inequality to the asymmetric setting. As an application, we…

Combinatorics · Mathematics 2025-11-04 Rebecca Carter

We give an upper bound on the maximal eigenvalue of the adjacency matrix of a connected graph in terms of its maximum degree, diameter and order. This bound is best possible up to a constant factor and improves prevoius results of…

Combinatorics · Mathematics 2007-05-23 Vladimir Nikiforov

We introduce an unsupervised graph embedding that trades off local node similarity and connectivity, and global structure. The embedding is based on a generalized graph Laplacian, whose eigenvectors compactly capture both network structure…

Machine Learning · Computer Science 2020-10-01 Shay Deutsch , Stefano Soatto

Let ${\mathbf T}_n$ be a uniformly random tree with vertex set $[n]=\{1,\ldots,n\}$, let $\Delta_{{\mathbf T}_n}$ be the largest vertex degree in ${\mathbf T}_n$, and let $\lambda_1({\mathbf T}_n),\ldots,\lambda_n({\mathbf T}_n)$ be the…

Probability · Mathematics 2024-04-03 Louigi Addario-Berry , Gábor Lugosi , Roberto Imbuzeiro Oliveira

Recent studies have experimentally shown that we can achieve in non-Euclidean metric space effective and efficient graph embedding, which aims to obtain the vertices' representations reflecting the graph's structure in the metric space.…

Machine Learning · Statistics 2023-05-16 Atsushi Suzuki , Atsushi Nitanda , Taiji Suzuki , Jing Wang , Feng Tian , Kenji Yamanishi

We derive Cheeger inequalities for directed graphs and hypergraphs using the reweighted eigenvalue approach that was recently developed for vertex expansion in undirected graphs [OZ22,KLT22,JPV22]. The goal is to develop a new spectral…

Data Structures and Algorithms · Computer Science 2022-11-18 Lap Chi Lau , Kam Chuen Tung , Robert Wang

The inducibility of a graph $H$ measures the maximum number of induced copies of $H$ a large graph $G$ can have. Generalizing this notion, we study how many induced subgraphs of fixed order $k$ and size $\ell$ a large graph $G$ on $n$…

Combinatorics · Mathematics 2019-11-05 Noga Alon , Dan Hefetz , Michael Krivelevich , Mykhaylo Tyomkyn

The number of embeddings of minimally rigid graphs in $\mathbb{R}^D$ is (by definition) finite, modulo rigid transformations, for every generic choice of edge lengths. Even though various approaches have been proposed to compute it, the gap…

Algebraic Geometry · Mathematics 2020-01-24 Evangelos Bartzos , Ioannis Emiris , Jan Legerský , Elias Tsigaridas

The maximum number of vertices in a graph of maximum degree $\Delta\ge 3$ and fixed diameter $k\ge 2$ is upper bounded by $(1+o(1))(\Delta-1)^{k}$. If we restrict our graphs to certain classes, better upper bounds are known. For instance,…

Combinatorics · Mathematics 2015-12-14 Eran Nevo , Guillermo Pineda-Villavicencio , David R. Wood

The article considers an inhomogeneous Erd\H{o}s-R\"enyi random graph on $\{1,\ldots, N\}$, where an edge is placed between vertices $i$ and $j$ with probability $\varepsilon_N f(i/N,j/N)$, for $i\le j$, the choice being made independent…

Probability · Mathematics 2024-02-28 Arijit Chakrabarty , Sukrit Chakraborty , Rajat Subhra Hazra

A set of colored graphs are compatible, if for every color $i$, the number of vertices of color $i$ is the same in every graph. A simultaneous embedding of $k$ compatibly colored graphs, each with $n$ vertices, consists of $k$ planar…

Computational Geometry · Computer Science 2021-01-19 Debajyoti Mondal

We analyze the convergence of the spectrum of large random graphs to the spectrum of a limit infinite graph. We apply these results to graphs converging locally to trees and derive a new formula for the Stieljes transform of the spectral…

Probability · Mathematics 2009-05-05 Charles Bordenave , Marc Lelarge