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Partitioning graphs into blocks of roughly equal size such that few edges run between blocks is a frequently needed operation in processing graphs. Recently, size, variety, and structural complexity of these networks has grown dramatically.…

Data Structures and Algorithms · Computer Science 2018-10-16 Yaroslav Akhremtsev , Peter Sanders , Christian Schulz

In this paper, we present, to our knowledge, the first known I/O efficient solutions for computing the k-bisimulation partition of a massive directed graph, and performing maintenance of such a partition upon updates to the underlying…

Databases · Computer Science 2013-05-03 Yongming Luo , George H. L. Fletcher , Jan Hidders , Yuqing Wu , Paul De Bra

The discrete Cheeger inequality, due to Alon and Milman (J. Comb. Theory Series B 1985), is an indispensable tool for converting the combinatorial condition of graph expansion to an algebraic condition on the eigenvalues of the graph…

Combinatorics · Mathematics 2023-04-19 Akhil Jalan

A basic fact in algebraic graph theory is that the number of connected components in an undirected graph is equal to the multiplicity of the eigenvalue 1 in the normalized adjacency matrix of the graph. In particular, the graph is…

Data Structures and Algorithms · Computer Science 2011-12-09 Shayan Oveis Gharan , Luca Trevisan

We study graph partitioning problems from a min-max perspective, in which an input graph on n vertices should be partitioned into k parts, and the objective is to minimize the maximum number of edges leaving a single part. The two main…

Data Structures and Algorithms · Computer Science 2011-10-21 Nikhil Bansal , Uriel Feige , Robert Krauthgamer , Konstantin Makarychev , Viswanath Nagarajan , Joseph , Naor , Roy Schwartz

Graph partitioning problems are a central topic of study in algorithms and complexity theory. Edge expansion and vertex expansion, two popular graph partitioning objectives, seek a $2$-partition of the vertex set of the graph that minimizes…

Data Structures and Algorithms · Computer Science 2019-10-22 Anand Louis , Rakesh Venkat

Let G=(V,E) be an undirected graph, lambda_k be the k-th smallest eigenvalue of the normalized laplacian matrix of G. There is a basic fact in algebraic graph theory that lambda_k > 0 if and only if G has at most k-1 connected components.…

Data Structures and Algorithms · Computer Science 2013-12-09 Shayan Oveis Gharan , Luca Trevisan

Let $G=(V, E)$ be a graph where $V$ and $E$ are the vertex and edge sets, respectively. For two disjoint subsets $A$ and $B$ of $V$, we say $A$ \emph{dominates} $B$ if every vertex of $B$ is adjacent to at least one vertex of $A$. A vertex…

Combinatorics · Mathematics 2023-08-04 Subhabrata Paul , Kamal Santra

We study the problem of edge partitioning, where the goal is to partition the edge set of a graph into several parts. The replication factor of a vertex $v$ is the number of parts that contain edges incident to $v$. The goal is to minimize…

Discrete Mathematics · Computer Science 2026-05-08 Alexander Yakunin , Andrey Kupavskii , Alexander Sushin , Stanislav Moiseev

Partitioning a graph into blocks of "roughly equal" weight while cutting only few edges is a fundamental problem in computer science with a wide range of applications. In particular, the problem is a building block in applications that…

Data Structures and Algorithms · Computer Science 2021-05-06 Lars Gottesbüren , Tobias Heuer , Peter Sanders , Christian Schulz , Daniel Seemaier

A new, constructive proof with a small explicit constant is given to the Erd\H{o}s-Pyber theorem which says that the edges of a graph on $n$ vertices can be partitioned into complete bipartite subgraphs so that every vertex is covered at…

Combinatorics · Mathematics 2013-11-21 László Csirmaz , Péter Ligeti , Gábor Tardos

Balanced partitioning is often a crucial first step in solving large-scale graph optimization problems, e.g., in some cases, a big graph can be chopped into pieces that fit on one machine to be processed independently before stitching the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-10 Kevin Aydin , MohammadHossein Bateni , Vahab Mirrokni

An $(\epsilon,\phi)$-expander decomposition of a graph $G=(V,E)$ is a clustering of the vertices $V=V_{1}\cup\cdots\cup V_{x}$ such that (1) each cluster $V_{i}$ induces subgraph with conductance at least $\phi$, and (2) the number of…

Data Structures and Algorithms · Computer Science 2019-05-28 Yi-Jun Chang , Thatchaphol Saranurak

The Cheeger inequality for undirected graphs, which relates the conductance of an undirected graph and the second smallest eigenvalue of its normalized Laplacian, is a cornerstone of spectral graph theory. The Cheeger inequality has been…

Data Structures and Algorithms · Computer Science 2018-10-15 Yuichi Yoshida

A $k$-star is a complete bipartite graph $K_{1,k}$. For a graph $G$, a $k$-star decomposition of $G$ is a set of $k$-stars in $G$ whose edge sets partition the edge set of $G$. If we weaken this condition to only demand that each edge of…

Combinatorics · Mathematics 2021-09-29 Ajani De Vas Gunasekara , Daniel Horsley

As a generalization of the concept of the partition dimension of a graph, this article introduces the notion of the $k$-partition dimension. Given a nontrivial connected graph $G=(V,E)$, a partition $\Pi$ of $V$ is said to be a…

Combinatorics · Mathematics 2018-09-18 Alejandro Estrada-Moreno

Coboundary and cosystolic expansion are notions of expansion that generalize the Cheeger constant or edge expansion of a graph to higher dimensions. The classical Cheeger inequality implies that for graphs edge expansion is equivalent to…

Combinatorics · Mathematics 2021-02-11 Tali Kaufman , Izhar Oppenheim

There has been a recent explosion in the size of stored data, partially due to advances in storage technology, and partially due to the growing popularity of cloud-computing and the vast quantities of data generated. This motivates the need…

Data Structures and Algorithms · Computer Science 2012-12-06 Isabelle Stanton

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

We present a shared-memory algorithm to compute high-quality solutions to the balanced $k$-way hypergraph partitioning problem. This problem asks for a partition of the vertex set into $k$ disjoint blocks of bounded size that minimizes the…

Data Structures and Algorithms · Computer Science 2021-04-19 Lars Gottesbüren , Tobias Heuer , Peter Sanders , Sebastian Schlag