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In manifold learning, algorithms based on graph Laplacians constructed from data have received considerable attention both in practical applications and theoretical analysis. In particular, the convergence of graph Laplacians obtained from…

Machine Learning · Computer Science 2011-05-23 Xueyuan Zhou , Mikhail Belkin

This paper concerns discrete-time occupancy processes on a finite graph. Our results can be formulated in two theorems, which are stated for vertex processes, but also applied to edge process (e.g., dynamic random graphs). The first theorem…

Probability · Mathematics 2024-10-10 Davide Sclosa , Michel Mandjes , Christian Bick

Motivated by discrete Laplacian differential operators with various accuracy orders in numerical analysis, we introduce new matrices attached to a simple graph that can be considered graph Laplacians with higher accuracy. In particular, we…

Combinatorics · Mathematics 2025-04-09 Mary Yoon

Conditional lower bounds for dynamic graph problems has received a great deal of attention in recent years. While many results are now known for the fully-dynamic case and such bounds often imply worst-case bounds for the partially dynamic…

Data Structures and Algorithms · Computer Science 2016-05-04 Søren Dahlgaard

Many modern data analytics applications on graphs operate on domains where graph topology is not known a priori, and hence its determination becomes part of the problem definition, rather than serving as prior knowledge which aids the…

Information Theory · Computer Science 2020-01-03 Ljubisa Stankovic , Danilo Mandic , Milos Dakovic , Milos Brajovic , Bruno Scalzo , Shengxi Li , Anthony G. Constantinides

This thesis generalizes the differential operators on standard oriented graphs and oriented hypergraphs introduced in 10.1137/15M1022793 and arXiv:2007.00325. The extended concepts of gradients, adjoints and $p$-Laplacians for vertices and…

Combinatorics · Mathematics 2023-04-14 Ariane Fazeny

As large-scale graphs become increasingly more prevalent, it poses significant computational challenges to process, extract and analyze large graph data. Graph coarsening is one popular technique to reduce the size of a graph while…

Machine Learning · Computer Science 2021-02-03 Chen Cai , Dingkang Wang , Yusu Wang

We consider a Laplacian on periodic discrete graphs. Its spectrum consists of a finite number of bands. In a class of periodic 1-forms, i.e., functions defined on edges of the periodic graph, we introduce a subclass of minimal forms with a…

Spectral Theory · Mathematics 2019-05-28 E. Korotyaev , N. Saburova

The paper is a brief survey of some recent new results and progress of the Laplacian spectra of graphs and complex networks (in particular, random graph and the small world network). The main contents contain the spectral radius of the…

Combinatorics · Mathematics 2011-11-15 Ya-Hong Chen , Rong-Ying Pan , Xiao-Dong Zhang

Many variants of join operations of graphs have been introduced and their spectral properties have been studied extensively by many researchers. This paper mainly focuses on the Laplacian spectra of some double join operations of graphs. We…

Combinatorics · Mathematics 2017-05-04 Gui-Xian Tian , Jing-Xiang He , Shu-Yu Cui

This paper is concerned with structures of general graphs with perfect matchings. We first reveal a partially ordered structure among factor-components of general graphs with perfect matchings. Our second result is a generalization of…

Discrete Mathematics · Computer Science 2013-03-26 Nanao Kita

For any graph, we define a rank-1 operator on a bipartite tensor product space, with components associated to the set of vertices and edges respectively. We show that the partial traces of the operator are the Laplacian and the…

Combinatorics · Mathematics 2013-05-01 Niel de Beaudrap , Vittorio Giovannetti , Simone Severini , Richard Wilson

We introduce and study a novel semi-random multigraph process, described as follows. The process starts with an empty graph on $n$ vertices. In every round of the process, one vertex $v$ of the graph is picked uniformly at random and…

{\em Partial domination problem} is a generalization of the {\em minimum dominating set problem} on graphs. Here, instead of dominating all the nodes, one asks to dominate at least a fraction of the nodes of the given graph by choosing a…

Computational Geometry · Computer Science 2025-05-23 Madhura Dutta , Anil Maheshwari , Subhas C. Nandy , Bodhayan Roy

We consider a database composed of a set of conceptual graphs. Using conceptual graphs and graph homomorphism it is possible to build a basic query-answering mechanism based on semantic search. Graph homomorphism defines a partial order…

Data Structures and Algorithms · Computer Science 2012-07-13 Abdurashid Mamadolimov

In communication field, an important issue is to group users and base stations to as many as possible subnetworks satisfying certain interference constraints. These problems are usually formulated as a graph partition problems which…

Combinatorics · Mathematics 2020-09-30 Chicheng Ma , Yucong Tang , Guanghui Wang , Guiying Yan , Bo Bai

This work introduces a novel algorithm for finding the connected components of a graph where the vertices and edges are grouped into sets defining a Set--Based Graph. The algorithm, under certain restrictions on those sets, has the…

Data Structures and Algorithms · Computer Science 2020-11-30 Ernesto Kofman , Denise Marzorati , Joaquín Fernández

We exploit a result by Nerman which shows that conditional limit theorems hold when a certain monotonicity condition is satisfied. Our main result is an application to vertex degrees in random graphs, where we obtain asymptotic normality…

Probability · Mathematics 2009-09-29 Svante Janson

Graph symmetries intervene in diverse applications, from enumeration, to graph structure compression, to the discovery of graph dynamics (e.g., node arrival order inference). Whereas Erd\H{o}s-R\'enyi graphs are typically asymmetric, real…

Probability · Mathematics 2018-12-27 Tomasz Luczak , Abram Magner , Wojciech Szpankowski

In latent-position random graph models (LPMs), latent vertex positions $U_{1},\ldots,U_{n}$ are sampled from some distribution on a latent space $\Omega$, then edges of an observed graph $G = ([n],E)$ are sampled with some probability…

Statistics Theory · Mathematics 2026-05-27 Jeannette Janssen , Na Lin , Aaron Smith