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A common way of partitioning graphs is through minimum cuts. One drawback of classical minimum cut methods is that they tend to produce small groups, which is why more balanced variants such as normalized and ratio cuts have seen more…

Machine Learning · Computer Science 2024-10-07 Chakib Fettal , Lazhar Labiod , Mohamed Nadif

The sparsest cut problem consists of identifying a small set of edges that breaks the graph into balanced sets of vertices. The normalized cut problem balances the total degree, instead of the size, of the resulting sets. Applications of…

Social and Information Networks · Computer Science 2017-02-17 Arlei Silva , Ambuj Singh , Ananthram Swami

The Multicut problem asks for a minimum cut separating certain pairs of vertices: formally, given a graph $G$ and demand graph $H$ on a set $T\subseteq V(G)$ of terminals, the task is to find a minimum-weight set $C$ of edges of $G$ such…

Computational Complexity · Computer Science 2025-04-16 Jacob Focke , Florian Hörsch , Shaohua Li , Dániel Marx

Given an unweighted tree $T=(V,E)$ with terminals $K \subset V$, we show how to obtain a $2$-quality vertex flow and cut sparsifier $H$ with $V_H = K$. We prove that our result is essentially tight by providing a $2-o(1)$ lower-bound on the…

Data Structures and Algorithms · Computer Science 2016-12-12 Gramoz Goranci , Harald Raecke

We introduce a new algorithmic framework for designing dynamic graph algorithms in minor-free graphs, by exploiting the structure of such graphs and a tool called vertex sparsification, which is a way to compress large graphs into small…

Data Structures and Algorithms · Computer Science 2017-12-19 Gramoz Goranci , Monika Henzinger , Pan Peng

We study deterministic algorithms for computing graph cuts, with focus on two fundamental problems: balanced sparse cut and $k$-vertex connectivity for small $k$ ($k=O(\polylog n)$). Both problems can be solved in near-linear time with…

Data Structures and Algorithms · Computer Science 2019-10-21 Yu Gao , Jason Li , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak , Sorrachai Yingchareonthawornchai

Graph sparsification is a technique that approximates a given graph by a sparse graph with a subset of vertices and/or edges. The goal of an effective sparsification algorithm is to maintain specific graph properties relevant to the…

Databases · Computer Science 2023-11-22 Yuhan Chen , Haojie Ye , Sanketh Vedula , Alex Bronstein , Ronald Dreslinski , Trevor Mudge , Nishil Talati

Given an n-vertex graph G, a drawing of G in the plane is a mapping of its vertices into points of the plane, and its edges into continuous curves, connecting the images of their endpoints. A crossing in such a drawing is a point where two…

Data Structures and Algorithms · Computer Science 2010-10-20 Julia Chuzhoy , Yury Makarychev , Anastasios Sidiropoulos

The (non-uniform) sparsest cut problem is the following graph-partitioning problem: given a "supply" graph, and demands on pairs of vertices, delete some subset of supply edges to minimize the ratio of the supply edges cut to the total…

Data Structures and Algorithms · Computer Science 2021-06-01 Vincent Cohen-Addad , Anupam Gupta , Philip N. Klein , Jason Li

We consider a the minimum k-way cut problem for unweighted graphs with a size bound s on the number of cut edges allowed. Thus we seek to remove as few edges as possible so as to split a graph into k components, or report that this requires…

Discrete Mathematics · Computer Science 2011-01-27 Ken-ichi Kawarabayashi , Mikkel Thorup

In the $0$-Extension problem, we are given an edge-weighted graph $G=(V,E,c)$, a set $T\subseteq V$ of its vertices called terminals, and a semi-metric $D$ over $T$, and the goal is to find an assignment $f$ of each non-terminal vertex to a…

Data Structures and Algorithms · Computer Science 2024-01-19 Yu Chen , Zihan Tan

Let \phi(G) be the minimum conductance of an undirected graph G, and let 0=\lambda_1 <= \lambda_2 <=... <= \lambda_n <= 2 be the eigenvalues of the normalized Laplacian matrix of G. We prove that for any graph G and any k >= 2, \phi(G) =…

Data Structures and Algorithms · Computer Science 2013-01-24 Tsz Chiu Kwok , Lap Chi Lau , Yin Tat Lee , Shayan Oveis Gharan , Luca Trevisan

A minimum path cover (MPC) of a directed acyclic graph (DAG) $G = (V,E)$ is a minimum-size set of paths that together cover all the vertices of the DAG. Computing an MPC is a basic polynomial problem, dating back to Dilworth's and…

Data Structures and Algorithms · Computer Science 2021-07-14 Manuel Cáceres , Massimo Cairo , Brendan Mumey , Romeo Rizzi , Alexandru I. Tomescu

In this paper we initiate the study of expander decompositions of a graph $G=(V, E)$ in the streaming model of computation. The goal is to find a partitioning $\mathcal{C}$ of vertices $V$ such that the subgraphs of $G$ induced by the…

Data Structures and Algorithms · Computer Science 2023-08-04 Arnold Filtser , Michael Kapralov , Mikhail Makarov

Given a graph $G$ and a set of terminals $T$, a \emph{distance emulator} of $G$ is another graph $H$ (not necessarily a subgraph of $G$) containing $T$, such that all the pairwise distances in $G$ between vertices of $T$ are preserved in…

Data Structures and Algorithms · Computer Science 2018-07-05 Hsien-Chih Chang , Paweł Gawrychowski , Shay Mozes , Oren Weimann

In graph sparsification, the goal has almost always been of {global} nature: compress a graph into a smaller subgraph ({sparsifier}) that maintains certain features of the original graph. Algorithms can then run on the sparsifier, which in…

Data Structures and Algorithms · Computer Science 2021-05-06 Shay Solomon

We consider the problem of finding a minimum cut of a weighted graph presented as a single-pass stream. While graph sparsification in streams has been intensively studied, the specific application of finding minimum cuts in streams is less…

Data Structures and Algorithms · Computer Science 2024-12-09 Matthew Ding , Alexandro Garces , Jason Li , Honghao Lin , Jelani Nelson , Vihan Shah , David P. Woodruff

Recently, Kawarabayashi and Thorup presented the first deterministic edge-connectivity recognition algorithm in near-linear time. A crucial step in their algorithm uses the existence of vertex subsets of a simple graph $G$ on $n$ vertices…

Combinatorics · Mathematics 2019-10-29 On-Hei Solomon Lo , Jens M. Schmidt , Mikkel Thorup

We study how to sparsify connectivity in graphs under a tight deletion budget. Given a graph $G$ and integers $k,x \ge 0$, Critical Node Cut (CNC) asks whether we can delete at most $k$ vertices so that the number of remaining unordered…

Data Structures and Algorithms · Computer Science 2026-02-17 Dušan Knop , Nikolaos Melissinos , Manolis Vasilakis

We show the existence of O(f(c)k) sized vertex sparsifiers that preserve all edge-connectivity values up to c between a set of k terminal vertices, where f(c) is a function that only depends on c, the edge-connectivity value. This…

Data Structures and Algorithms · Computer Science 2019-10-24 Yang P. Liu , Richard Peng , Mark Sellke