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相关论文: Vertex Sparsifiers for c-Edge Connectivity

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We define a general variant of the graph clustering problem where the criterion of density for the clusters is (high) connectivity. In {\sc Clustering to Given Connectivities}, we are given an $n$-vertex graph $G$, an integer $k$, and a…

数据结构与算法 · 计算机科学 2018-04-23 Petr A. Golovach , Dimitrios M. Thilikos

We revisit the problem of fault-tolerant (FT) distance preservers, when failure events in the network admit a form of correlation modeled as color faults. FT distance preservers are sparse subgraphs that preserve distances between specified…

数据结构与算法 · 计算机科学 2026-05-01 Merav Parter , Asaf Petruschka

\textsc{Densest $k$-Subgraph} is the problem to find a vertex subset $S$ of size $k$ such that the number of edges in the subgraph induced by $S$ is maximized. In this paper, we show that \textsc{Densest $k$-Subgraph} is fixed parameter…

数据结构与算法 · 计算机科学 2022-07-21 Tesshu Hanaka

We consider the fundamental problems of determining the rooted and global edge and vertex connectivities (and computing the corresponding cuts) in directed graphs. For rooted (and hence also global) edge connectivity with small integer…

数据结构与算法 · 计算机科学 2021-04-16 Chandra Chekuri , Kent Quanrud

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…

数据结构与算法 · 计算机科学 2020-11-30 Ernesto Kofman , Denise Marzorati , Joaquín Fernández

Recent years have seen extensive research on directed graph sparsification. In this work, we initiate the study of fast fully dynamic spectral and cut sparsification algorithms for directed graphs. We introduce a new notion of spectral…

数据结构与算法 · 计算机科学 2025-07-29 Yibin Zhao

In this paper, we present new incremental algorithms for maintaining data structures that represent all connectivity cuts of size one in directed graphs (digraphs), and the strongly connected components that result by the removal of each of…

数据结构与算法 · 计算机科学 2018-03-01 Loukas Georgiadis , Giuseppe F. Italiano , Nikos Parotsidis

In the k-Disjoint Shortest Paths problem, a set of terminal pairs of vertices $\{(s_i,t_i)\mid 1\le i\le k\}$ is given and we are asked to find paths $P_1,\ldots,P_k$ such that each path $P_i$ is a shortest path from $s_i$ to $t_i$ and…

数据结构与算法 · 计算机科学 2021-07-08 Saeed Akhoondian Amiri , Julian Wargalla

Graphlets of order $k$ in a graph $G$ are connected subgraphs induced by $k$ nodes (called $k$-graphlets) or by $k$ edges (called edge $k$-graphlets). They are among the interesting subgraphs in network analysis to get insights on both the…

数据结构与算法 · 计算机科学 2025-05-15 Alessio Conte , Roberto Grossi , Yasuaki Kobayashi , Kazuhiro Kurita , Davide Rucci , Takeaki Uno , Kunihiro Wasa

We show a deterministic algorithm for computing edge connectivity of a simple graph with $m$ edges in $m^{1+o(1)}$ time. Although the fastest deterministic algorithm by Henzinger, Rao, and Wang [SODA'17] has a faster running time of…

数据结构与算法 · 计算机科学 2020-08-20 Thatchaphol Saranurak

We present faster algorithms for computing the 2-edge and 2-vertex strongly connected components of a directed graph, which are straightforward generalizations of strongly connected components. While in undirected graphs the 2-edge and…

数据结构与算法 · 计算机科学 2018-03-02 Monika Henzinger , Sebastian Krinninger , Veronika Loitzenbauer

Contraction of an edge merges its end points into a new vertex which is adjacent to each neighbor of the end points of the edge. An edge in a $k$-connected graph is {\em contractible} if its contraction does not result in a graph of lower…

离散数学 · 计算机科学 2009-02-10 N. S. Narayanaswamy , N. Sadagopan , Apoorve Dubey

For a family of graphs $\mathcal{G}$, the $\mathcal{G}$-\textsc{Contraction} problem takes as an input a graph $G$ and an integer $k$, and the goal is to decide if there exists $F \subseteq E(G)$ of size at most $k$ such that $G/F$ belongs…

离散数学 · 计算机科学 2020-08-19 Saket Saurabh , Uéverton dos Santos Souza , Prafullkumar Tale

Our work concerns algorithms for an unweighted variant of Maximum Flow. In the All-Pairs Connectivity (APC) problem, we are given a graph $G$ on $n$ vertices and $m$ edges, and are tasked with computing the maximum number of edge-disjoint…

数据结构与算法 · 计算机科学 2023-05-04 Shyan Akmal , Ce Jin

We describe a synchronous distributed algorithm which identifies the edge-biconnected components of a connected network. It requires a leader, and uses messages of size O(log |V|). The main idea is to preorder a BFS spanning tree, and then…

分布式、并行与集群计算 · 计算机科学 2007-05-23 David Pritchard

Connectivity (or equivalently, unweighted maximum flow) is an important measure in graph theory and combinatorial optimization. Given a graph $G$ with vertices $s$ and $t$, the connectivity $\lambda(s,t)$ from $s$ to $t$ is defined to be…

数据结构与算法 · 计算机科学 2024-12-25 Shyan Akmal

We propose an approach to graph sparsification based on the idea of preserving the smallest $k$ eigenvalues and eigenvectors of the Graph Laplacian. This is motivated by the fact that small eigenvalues and their associated eigenvectors tend…

离散数学 · 计算机科学 2023-06-13 Catherine Babecki , Stefan Steinerberger , Rekha R. Thomas

We study the VC-dimension of the set system on the vertex set of some graph which is induced by the family of its $k$-connected subgraphs. In particular, we give tight upper and lower bounds for the VC-dimension. Moreover, we show that…

离散数学 · 计算机科学 2016-02-03 Andrea Munaro

How might one "reduce" a graph? That is, generate a smaller graph that preserves the global structure at the expense of discarding local details? There has been extensive work on both graph sparsification (removing edges) and graph…

离散数学 · 计算机科学 2020-02-18 Gecia Bravo-Hermsdorff , Lee M. Gunderson

Given a large graph $G$ with a subset $|T|=k$ of its vertices called terminals, a quality-$q$ flow sparsifier is a small graph $G'$ that contains $T$ and preserves all multicommodity flows that can be routed between terminals in $T$, to…

数据结构与算法 · 计算机科学 2023-10-13 Yu Chen , Zihan Tan